Dissertations / Theses on the topic 'Cooperative distributed control'

Au cours des dernières années, le réseau électrique connait une transformation rapide avec la pénétration massive des unités de production renouvelables et distribuées. Le concept de microgrids (micro-réseau électrique) est un élément clés de cette transition énergétique. Ces micro-réseaux sont constitués par un ensemble de plusieurs unités de production distribuées (DGUs), d'unités de stockage (SUs) et de charges interconnectées par des lignes électriques. Un microgrid peut être installé dans plusieurs endroits, par exemple dans des maisons, des hôpitaux, des quartiers, etc. et fonctionne soit en mode connecté au réseau principale, soit en mode isolé (autonome). Les microgrids sont confrontés à plusieurs défis liés à la garantie de la stabilité, la cybersécurité, l'optimisation des coûts énergétiques, la gestion de l'énergie, la qualité de l'énergie, etc. Dans ce travail, nous concentrons notre attention sur le contrôle des microgrids à courant continu en mode de fonctionnement autonome. La principale contribution de cette thèse est l’établissement de lois de commande par retour d’état distribuées assurant un partage de courant proportionnel entre les unités de production, une régulation de la tension moyenne des lignes et un équilibrage simultané des états de charge des éléments de stockage. En partant de l'hypothèse que les agents (DGU ou SU) ont les mêmes paramètres physiques, la preuve de la convergence exponentielle et globale est donnée en l’absence d’une connaissance de la charge présente sur le réseau. La thèse est divisée en trois parties. La première partie présente le concept des microgrids, un état de l’art sur leurs stratégies de contrôle et les préliminaires mathématiques nécessaires tout au long du manuscrit. La deuxième partie constitue la contribution théorique de cette thèse et aborde la synthèse de lois de contrôle distribuées, garantissant les objectifs envisagés en l’absence d’une connaissance de la charge variable sur le réseau et même en cas de perturbation constantes au niveau de l’entrée de commande. Cette garantie est apportée en considérant trois actions intégrales distribuées de type consensus. Dans la troisième partie, les contrôleurs proposés sont évalués dans différents scénarios par le biais de simulation Matlab/Simulink et de tests Hardware-in-the-Loop (HIL) en temps réel. Les résultats montrent que les objectifs de contrôle sont atteints avec succès, ce qui illustre l'efficacité de la méthodologie de contrôle proposée
In recent years, the power grid has undergone a rapid transformation with the massive penetration of renewable and distributed generation units. The concept of microgrids is a key element of this energy transition. Microgrids are made up of a set of several distributed generation units (DGUs), storage units (SUs) and loads interconnected by power lines. A microgrid can be installed in several locations, for example in houses, hospitals, a neighborhood or village, etc., and operates either in connected mode to the main grid or in isolated (autonomous) mode. Microgrids are facing several challenges related to stability assurance, cyber-security, energy cost optimization, energy management, power quality, etc. In this work, we focus our attention on the control of islanded direct current microgrids. The main contribution is the design of a new distributed control approach to provably achieve current sharing, average voltage regulation and state-of-charge balancing simultaneously with global exponential convergence. The main tools are consensus in multi-agent systems, passivity, Lyapunov stability, linear matrix inequalities, etc. The thesis is divided into three parts. The First part presents the concept of microgrids, a literature review of their control strategies and the mathematical preliminaries required throughout the manuscript. The second part deals with the design of the proposed distributed control approach to achieve the considered objectives. The system is augmented with three distributed consensus-like integral actions, and a distributed-based static state feedback control architecture is proposed. Starting from the assumption that the agents (DGUs or SUs) have the same physical parameters, we provide proof of global exponential convergence. Moreover, the proposed control approach is distributed, i.e., each agent exchange relative information with only its neighbors through sparse communication networks. The proposed controllers do not need any information about the parameters of the power lines neither the topology of the microgrid. The control objectives are reached despite the unknown load variation and constant disturbances. In the third part, the proposed distributed controllers are assessed in different scenarios through Matlab/Simulink simulation and real-time Hardware-in-the-Loop experiment. The results show that the control objectives are successfully achieved, illustrating the effectiveness of the proposed control methodology

Cette thèse considère principalement trois problèmes dans le domaine du contrôle distribué coopératif des systèmes multi-agents(SMA): le consensus, la navigation en formation et le maintien en formation d'un groupe d'agents lorsqu'un agent disparait. Nous proposons 3 algorithmes pour résoudre le problème du calcul distribué d'un consensus à partir de l'approche leadeur-suiveur dans le contexte SMA à dynamique non-linéaire. La référence est définie comme un leader virtuel dont on n'obtient, localement, que les données de position et de vitesse. Pour résoudre le problème du suivi par consensus pour les SMA à dynamique non-linéaire, nous considérons le suivi par consensus pour SMA de premier ordre. On propose des résultats permettant aux suiveurs de suivre le leadeur virtuel en temps fini en ne considérant que les positions des agents. Ensuite, nous considérons le suivi par consensus de SMA de second. Dans le cas de la planification de trajectoire et la commande du mouvement de la formation multi-agents. L'idée est d'amener la formation, dont la dynamique est supposée être en 3D, d'une configuration initiale vers une configuration finale (trouver un chemin faisable en position et orientation) en maintenant sa forme tout le long du chemin en évitant les obstacles. La stratégie proposée se décompose en 3 étapes. Le problème du Closing-Rank se traduit par la réparation d'une formation rigide multi-agents "endommagée" par la perte de l'un de ses agents. Nous proposons 2 algorithmes d'autoréparation systématique pour récupérer la rigidité en cas de perte d'un agent. Ces réparations s'effectuent de manière décentralisée et distribuée n'utilisant que des informations de voisinage.

In this thesis, a distributed extremum seeking and cooperative control algorithm is designed for mobile agents to disperse themselves optimally in maintaining communication quality and maximizing their coverage. The networked mobile agents locally form a virtual multiple-input multiple-output (MIMO) communication system, and they cooperatively communicate among them by using the decode and forward cooperative communication technique. The outage probability is used as the measure of communication quality, and it can be estimated real-time. A general performance index balancing outage probability and spatial dispersion is chosen for the overall system. The extremum seeking control approach is used to estimate and optimize the value of the performance index, and the cooperative formation control is applied to move the mobile agents to achieve the optimal solution by using only the locally-available information. Through the integration of cooperative communication and cooperative control, network connectivity and coverage of the mobile agents are much improved when compared to either non-cooperative communication approaches or other existing control results. Analytical analysis is carried out to demonstrate the performance and robustness of the proposal methodology, and simulation is done to illustrate its effectiveness.
M.S.E.E.
Masters
Electrical Engineering and Computing
Engineering and Computer Science
Electrical Engineering

A variety of cooperative medium access control (MAC) schemes are designed for the sake of improving the achievable transmit rate and for reducing the transmit energy dissipation of cooperative communication systems relying on realistic greedy - rather than altruistic - relay nodes (RNs). Based on the system’s objective functions (OF), novel distributed relay selection schemes are developed for selecting the best relay node (RN) set. In order to investigate the effect of the proposed MAC schemes on the performance of the cooperative communication systems considered, the system’s stability is analysed with the aid of queueing theory. Specifically, we first consider a cooperative spectrum leasing system (CSLS) supporting a licensed source node (SN) and a licensed destination node (DN) as well as multiple unlicensed greedy RNs, which require rewards for providing cooperative transmission assistance. A ’win-win’ (WW) cooperative framework (WWCF) is formulated for sake of improving the achievable transmit rate and for simulanteously minimizing the energy dissipation of the co- operative spectrum leasing system considered. Based on the proposed WWCF, the licensed SN intends to lease part of its spectrum to the unlicensed RNs in exchange for cooperative support, leading to an improved transmit rate, while simultaneously reducing the transmit power. The unlicensed RNs also have an incentive to provide cooperative transmission assistance for the SN, since in exchange for relaying assistance they are allowed to access the licensed spectrum for transmitting their own data, and even to maintain their own target Quality of Service (QoS). Furthermore, a distributed WW cooperative MAC protocol is developed for implementing the proposed WWCF by designing a specific signalling procedure and the format of both the data frame control messages as well as a distributed relay selection scheme. More explicitly, a novel backoff algorithm is designed for distributively selecting the best RN in order to optimize the system’s OF formulated by our WWCF. Our simulation results demonstrated that both substantial rate improvements and considerable energy savings are achieved by implementing the proposed distributed WW cooperative MAC protocol. However, encountering a low service rate at the MAC layer may excessively increase the length of queue in the buffer storing the incoming packet. Hence, the queueing system may become unstable due to the low service rate limited by an inferior MAC protocol design. Hence we conceived a queueing model for our cooperative spectrum leasing system relying on the proposed distributed WW cooperative MAC protocol. In order to simplify the stability analysis, some idealized simplifying assumptions are invoked and a non-Markovian analysis method is used for investigating the transmission probability of each node and for deriving the average departure rates at both the SN and the RNs operating under the control of the proposed distributed WW cooperative MAC protocol. Our simulation results confirmed that an increased stable throughput is provided by the proposed distributed WW cooperative MAC protocol for both the SN and RNs compared to the benchmark schemes. As an improved extension of the proposed WWCF, a WW reciprocal-selection-based framework (WWRSF) is formulated for a cooperative spectrum leasing system hosting multiple licensed transmission pairs and multiple unlicensed transmission pairs. The SN of a licensed pair of nodes is referred as the primary transmitter (PT), while the SN of an unlicensed transmission pair is termed as the secondary transmitter (ST). Based on the proposed WWRSF, the PT intends to lease its spectral resources to an appropriate secondary transmitter (ST) in exchange for cooperative transmission assistance for the sake of minimizing its transmit power and simultaneously satisfying its transmit rate requirement. The ST has an incentive to collaborate with the best PT for the sake of minimizing the ST’s transmit power under the constraint of its QoS requirement, whilst simultaneously winning a transmission opportunity for its own traffic. Based on the OFs of the proposed WWRSF, a distributed WW reciprocal-selection-based medium access scheme (DWWRS-MAS) is designed, which is capable of producing the best cooperative pairs set for the sake of reducing the transmit power of both the PT and of the ST in each cooperative pair, whilst simultaneously satisfying their transmit rate requirements. This is achieved with the aid of the proposed distributed reciprocal selection between the active PTs and STs, which have the capability of providing successful cooperative transmission assistance. Moreover, we analyse both the queueing stability and the algorithmic stability of our cooperative spectrum leasing system exploiting our DWWRS-MAS. In comparison to the benchmark schemes considered in the literature, the proposed DWWRS-MAS is capable of achieving a performance, which is comparable to that of the optimal schemes in terms of the system’s transmit power and system’s achievable transmit rate.

The major objective of this dissertation is extending the capabilities of game theoretic distributed control to more general settings. In particular, we are interested in drifting environments and/or constrained communications. The first part of the dissertation concerns slowly varying dynamics, i.e., drifting environments. A standard assumption in game theoretic learning is a stationary environment, e.g., the game is fixed. We investigate the case of slow variations and show that for sufficiently slow time variations, the limiting behavior “tracks” the stochastically stable states. Since the analysis is regarding Markov processes, the results could be applied to various game theoretic learning rules. In this research, the results were applied to log-linear learning. A mobile sensor coverage example was tested in both simulation and laboratory experiments. The second part considers a problem of coordinating team players' actions without any communications in team-based zero-sum games. Generally, some global signalling devices are required for common randomness between players, but communications are very limited or impossible in many practical applications. Instead of learning a one-shot strategy, we let players coordinate a periodic sequence of deterministic actions and put an assumption on opponent's rationality. Since team players' action sequences are periodic and deterministic, common randomness is no longer required to coordinate players. It is proved that if a length of a periodic action sequence is long enough, then opponents with limited rationality cannot recognize its pattern. Because the opponents cannot recognize that the players are playing deterministic actions, the players' behavior looks like a correlated and randomized joint strategy with empirical distribution of their action sequences. Consequently players can coordinate their action sequences without any communications or global signals, and the resulting action sequences have correlated behavior. Moreover, the notion of micro-players are introduced for efficient learning of long action sequences. Micro-player matching approach provides a new framework that converts the original team-based zero-sum game to a game between micro-players. By introducing a de Bruijn sequence to micro-player matching, we successfully separate the level of opponent's rationality and the size of the game of micro-players. The simulation results are shown to demonstrate the performance of micro-player matching methods. Lastly, the results of the previous two topics are combined by considering a problem of coordinating actions without communications in drifting environments. More specifically, it is assumed that the opponent player in the team-based zero-sum games tries to adjust its strategy in the set of bounded recall strategies. Then the time-varying opponent's strategy can be considered as a dynamic environment parameter in a coordination game between the team players. Additionally, we develop a human testbed program for further study regarding a human as an adaptive opponent in the team-based zero-sum games. The developed human testbed program can be a starting point for studying game theoretic correlated behavior learning against a human.

In this thesis, a tube-based Distributed Economic Predictive Control (DEPC) scheme is presented for a group of dynamically coupled linear subsystems. These subsystems are components of a large scale system and control inputs are computed based on optimizing a local economic objective. Each subsystem is interacting with its neighbors by sending its future reference trajectory, at each sampling time. It solves a local optimization problem in parallel, based on the received future reference trajectories of the other subsystems. To ensure recursive feasibility and a performance bound, each subsystem is constrained to not deviate too much from its communicated reference trajectory. This difference between the plan trajectory and the communicated one is interpreted as a disturbance on the local level. Then, to ensure the satisfaction of both state and input constraints, they are tightened by considering explicitly the effect of these local disturbances. The proposed approach averages over all possible disturbances, handles tightened state and input constraints, while satisfies the compatibility constraints to guarantee that the actual trajectory lies within a certain bound in the neighborhood of the reference one. Each subsystem is optimizing a local arbitrary economic objective function in parallel while considering a local terminal constraint to guarantee recursive feasibility. In this framework, economic performance guarantees for a tube-based distributed predictive control (DPC) scheme are developed rigorously. It is presented that the closed-loop nominal subsystem has a robust average performance bound locally which is no worse than that of a local robust steady state. Since a robust algorithm is applying on the states of the real (with disturbances) subsystems, this bound can be interpreted as an average performance result for the real closed-loop system. To this end, we present our outcomes on local and global performance, illustrated by a numerical example.

Smart grid is more than just the smart meters. The future smart grids are expected to include a high penetration of distributed generations (DGs), most of which will consist of renewable energy sources, such as solar or wind energy. It is believed that the high penetration of DGs will result in the reduction of power losses, voltage profile improvement, meeting future load demand, and optimizingthe use of non-conventionalenergy sources. However, more serious problems will arise if a decent control mechanism is not exploited. An improperly managed high PV penetration may cause voltage profile disturbance, conflict with conventional network protection devices, interfere with transformer tap changers, and as a result, cause network instability. Indeed, it is feasible to organize DGs in a microgrid structure which will be connected to the main grid through a point of common coupling (PCC). Microgrids are natural innovation zones for the smart grid because of their scalability and flexibility. A proper organization and control of the interaction between the microgrid and the smartgrid is a challenge. Cooperative control makes it possible to organize different agents in a networked system to act as a group and realize the designated objectives. Cooperative control has been already applied to the autonomous vehicles and this work investigates its application in controlling the DGs in a micro grid. The microgrid power objectives are set by a higher level control and the application of the cooperative control makes it possible for the DGs to utilize a low bandwidth communication network and realize the objectives. Initially, the basics of the application of the DGs cooperative control are formulated. This includes organizing all the DGs of a microgrid to satisfy an active and a reactive power objective. Then, the cooperative control is further developed by the introduction of clustering DGs into several groups to satisfy multiple power objectives. Then, the cooperative distribution optimization is introduced to optimally dispatch the reactive power of the DGs to realize a unified microgrid voltage profile and minimizethelosses. Thisdistributedoptimizationis agradient based techniqueand itis shown that when the communication is down, it reduces to a form of droop. However, this gradient based droop exhibits a superior performance in the transient response, by eliminating the overshoots caused by the conventional droop. Meanwhile, the interaction between each microgrid and the main grid can be formulated as a Stackelberg game. The main grid as the leader, by offering proper energy price to the micro grid, minimizes its cost and secures the power. This not only optimizes the economical interests of both sides, the microgrids and the main grid, but also yields an improved power flow and shaves the peak power. As such, a smartgrid may treat microgrids as individually dispatchable loads or generators.
Ph.D.
Doctorate
Electrical Engineering and Computer Science
Engineering and Computer Science
Electrical Engineering

Thesis (M.S. in Mechanical Engineering)--Naval Postgraduate School, June 2009.
Thesis Advisor(s): Lee, Deok Jin ; Kaminer, Issac I. "June 2009." Description based on title screen as viewed on 13 July 2009. Author(s) subject terms: Unmanned Aerial Vehicle, UAV, extremum seeking, simulink, high bandwidth communication links, SNR Model, coordinated control, cooperative control, decentralized control, wireless sensor network. Includes bibliographical references (p. 51). Also available in print.

Cette dissertation fait face au problème de la localisation de sources, un sujet qui a été largement étudié dans la littérature récente au vu de son grand nombre d'applications. En particulier, ce travail se concentre sur le pilotage de multiples capteurs, capables de prendre des mesures ponctuelles de la quantité émise, vers la source sans faire usage d'aucune information de position, qui se trouve être indisponible dans de nombreux cas pratiques (par exemple, sous l'eau ou dans l'exploration souterraine). En faisant quelques hypothèses sur le processus de diffusion, nous développons un modèle qui permet d'utiliser des outils mathématiques (l'intégrale de Poisson et ses dérivées) pour obtenir une simple approximation du gradient de la fonction décrivant le processus de diffusion, dont la source représente le maximum, ce qui permet d'utiliser l'algorithme du gradient et trouver l'emplacement de la source. Les contributions sont de trois ordres : d'abord, nous utilisons ces outils pour résoudre le problème de la recherche d'une source en deux dimensions à travers d'un contrôle centralisé, où un seul véhicule, équipé de multiples capteurs et sans information de position, se déplace dans un environnement planaire où se trouve une source. Ensuite, nous étendons cette recherche à un cadre en trois dimensions, en considérant un engin volant équipé de capteurs qui se déplace dans l'espace ; pour ce cas plus général, outre la validation par simulations, nous fournissons également une étude théorique des propriétes de convergence de la loi de commande proposée. Enfin, nous abordons le problème de la localisation de source de façon distribuée, compte tenu de plusieurs capteurs autonomes mobiles (en deux dimensions) ; outre le problème de mettre en oeuvre l'algorithme de localisation de source de manière distribuée, nous devons garantir un contrôle de la formation approprié pour assurer l'exactitude de l'estimation du gradient, et donc atteindre la source.}
The dissertation faces the problem of source localisation, a topic which has been extensively studied in recent literature due to its large number of applications. In particular, it focuses on steering multiple sensors, able to take point-wise measurements of the emitted quantity, towards the source without making use of any position information, which happens to be unavailable in many practical cases (for example, underwater or underground exploration). By making some assumptions on the diffusion process, we develop a model which allows us to use some mathematical tools (the Poisson integral and its derivatives) for a simple approximation of the gradient of the function describing the diffusion process, whose source represents its maximum, making it possible to perform a gradient ascent to find the source location. The contributions are threefold: first, we use such tools to solve a 2-dimensional centralised source-seeking problem, where a single vehicle, equipped with multiple sensors and without position information, is moving in a planar environment where a source is supposed to emit. Then, we extend it to a 3-dimensional framework, considering a flying vehicle equipped with sensors moving in the space; for this more general case, in addition to simulation validation, we provide a theoretical study of the convergence properties of the proposed control law. Finally, we tackle the distributed source-localisation problem, considering several autonomous moving sensors (in two dimensions); in addition to the problem of implementing the source-localisation algorithm in a distributed manner, in this latter case we have also to guarantee a suitable formation control, to ensure the correctness of the gradient estimation and hence reach the source

The significant decrease in manufacturing costs of hardware components for quadrotors has greatly encouraged research into the design of flight control algorithm for quadrotors, which has seen great growth in recent years. One of the key aspects of the research is the communication between the quadrotors. Nowadays it is considered essential that the quadrotors can communicate with each other. This feature allows numerous advantages: it is possible to generate a network capable of collaborating to solve complex tasks that single quadrotors would not be able to perform, or complete them in a shorter time. The objective of this thesis is the design of a distributed algorithm to control the navigation of a set of quadrotors flying through the same navigation space. A surveillance task has been chosen as a case study, where quadrotors are in charge of arranging themselves in order to protect a target from intruders. Each quadrotor needs to complete both a specific task assigned to it (prevent a certain intruders from reaching the target) and a task in common with the other quadrotors (make sure that the center of the drones coincides with the target and the quadrotors do not collide). With this goal in mind, the project starts with the design of the quadrotor model, controller and trajectories from scratch. Then a Distributed Model Predictive Control algorithm is designed ad hoc to control the navigation of quadrotors. One of the challenges in the creation of this algorithm is the adaptation of the control algorithm to the simultaneous use of Model Predictive Control (MPC) and Online Distributed Gradient Tracking (O-DGT). Indeed, the speed required for the optimization calculations led us to reformulate the MPC in order to make the calculations faster and thus satisfy the limits imposed by the chosen time-step. The proposed model is tested with numerical examples, analyzing a series of cases that allowed us to test different combinations of the developed algorithms.

In the last decades an increasing number of non linear and time variant loads has been connected to the distribution network, thus affecting voltage and power quality in transmission and distribution networks. On the other hand, there is an increasing demand for premium electric power, in terms of quality and reliability, calling for regulatory provisions to limit the harmonic and unbalance impact of loads and technical provisions to reduce voltage distortion and asymmetry. Moreover, following international policies toward environment-sustainable development, power sources making use of renewable energy are developing fast and become more and more diffused in electrical networks. In the coming years, we therefore expect a capillary distribution of electronic interfaces controlling the energy flow from distributed “green” power sources and the distribution network. A completely new scenario for energy generation and management will therefore appear, in a situation where the distribution backbone remains substantially unchanged. The work of this dissertation takes origin from the above context, which shows the need for coordinated operation of the various power sources and compensation equipment distributed in the grid, in a situation where the supply is affected by distortion and asymmetry and the loads pollute harmonics, reactive currents and phase unbalance. The goal of this work is to establish a theoretical background and to develop criteria and control algorithms to manage cooperatively a system of distributed electronic interfaces and compensation equipment, so as to optimize the network operation in terms of power quality and efficient use of energy. This means to face the issue of reactive, harmonic and unbalance compensation, not only at local level, as commonly done at the time of writing, but at a system level. The primary concern is to exploit every equipment at its best, while avoiding detrimental interactions among them. An innovative and comprehensive approach is presented here, which is capable to deal with actual networks (characterized by unbalance, distortion and asymmetry) and is developed in the distributed and cooperative perspective. In particular, supervision (global) and local control algorithms are developed, which apply to every type of compensation equipment, from Static VAR Compensators to Active Power Filters and Electronic Interfaces. The control approach lays on a set of conservative quantities, which keep their meaning irrespective of voltage level and phase shift and are therefore capable to provide a general descriptive and communication background of the electrical system. Several control techniques are analyzed, underlining their advantages and drawbacks, and eventually a simplified control method is developed which can easily be implemented and applies both to single-phase and three-phase systems. Such approach is analyzed in detail and extended to face the problems of unbalanced and asymmetrical systems. Several simulation results are provided to illustrate properties and operation of the solutions analyzed and developed in the various steps of the work.
Negli ultimi decenni il crescente numero di carichi non lineari e tempo-varianti collegati alla rete di distribuzione elettrica ha condizionato l’andamento della tensione e la qualità dell’energia nelle reti di trasmissione e distribuzione. Per contro si è parallelamente registrata un’importante domanda di potenza elettrica di elevata qualità, sia per quanto riguarda l’affidabilità della fornitura, sia per quanto riguarda il soddisfacimento di specifici requisiti sulle forme d’onda, il che ha richiesto interventi normativi per limitare l’inquinamento armonico e lo sbilanciamento dovuto ai carichi e provvedimenti tecnici per ridurre la distorsione di tensione e l’asimmetria. Inoltre, a seguito delle politiche internazionali per lo sviluppo sostenibile, i dispositivi che sfruttano l’energia delle fonti rinnovabili si stanno rapidamente sviluppando e stanno divenendo sempre più diffusi nelle reti elettriche. Viene così a delinearsi uno scenario completamente nuovo nella generazione e gestione dell’energia, che si inserisce però in una struttura della rete di distribuzione che rimane sostanzialmente inalterata rispetto al passato. Il presente lavoro di tesi nasce proprio in questo contesto e sottolinea la necessità di una gestione coordinata dei vari generatori e compensatori distribuiti in una rete elettrica, di per sé affetta da distorsione e asimmetria e ricca di carichi reattivi, distorcenti e sbilanciati. L’obiettivo della ricerca è quello di fornire una base teorica e sviluppare criteri e algoritmi di controllo per la gestione cooperativa di un sistema distribuito di interfacce elettroniche e sistemi di compensazione, così da ottimizzare il funzionamento della rete in termini di power quality ed efficienza nell’impiego dell’energia. Ciò significa affrontare il problema della compensazione armonica, reattiva e dello sbilanciamento, non più a livello locale, come a tutt’oggi viene fatto, ma piuttosto a livello di sistema. Il primo obbiettivo è quello di sfruttare ciascun compensatore al massimo delle proprie possibilità, evitando inoltre l’insorgere di risonanze o interazioni indesiderate tra le varie unità. Viene dunque presentato un approccio alla compensazione innovativo e completo, che risulta applicabile alle reti reali (caratterizzate da sbilanciamento, distorsione e asimmetria) ed è sviluppato nell’ottica distribuita e cooperativa. In particolar modo sono presentati diversi algoritmi di controllo, sia locali che centralizzati (globali), applicabili ad ogni tipo di compensatore, dagli Static Var Compensator ai filtri attivi di potenza e alle interfacce elettroniche. La strategia di controllo è basata su grandezze conservative, che mantengono uno specifico significato fisico indipendentemente dal livello di tensione e dallo sfasamento, risultando così un efficace mezzo per la descrizione e il trasferimento delle informazioni attraverso la rete elettrica. Vengono dunque analizzate diverse tecniche di controllo, sottolineandone vantaggi e svantaggi, fino ad arrivare ad una strategia semplificata, di implementazione particolarmente elementare e applicabile sia a sistemi monofase che trifase. Tale approccio è analizzato nel dettaglio e infine esteso alla considerazione di sistemi sbilanciati o asimmetrici. I risultati di numerose indagini simulative illustrano man mano proprietà e funzionamento delle varie soluzioni proposte.

This thesis analyzes various beamforming techniques and theories of space information networking (SIN), with the aim of merging and using them in real application. We propose then two algorithm to solve two different problem linked to satellites and beamforming. The first one show a cluster of satellites that performs collaborative beamforming to reach an Earth user, while reducing interference in secondary directions. Then we consider a problem for hybrid satellite-terrestrial relay networks (HSTRNs), where multiple geostationary satellites transmit signals to multiple Earth terminal, with the help of multiple single-antenna relays.

The upward trends in renewable energy deployment in recent years brings new challengesto the development of electrical networks. Interconnected microgrids appear as a novelbottom-up approach to the production and integration of renewable energy.Using model predictive control (MPC), the energy management of several interconnectedmicrogrids is investigated. An optimisation problem is formulated and distributed ontothe individual units using the alternating direction method of multipliers (ADMM). Themicrogrids cooperate to reach a global optimum using neighbour-to-neighbour communications.The benefits of using distributed operation control for microgrids are analysed and a controlarchitecture is proposed. Two algorithms are implemented to solve the optimisationproblem and their advantages or differences are confronted.
Förnybara energikällor har ökat under senaste åren. Det innebär nya utmaningar förevolutionen av elektriska nät. Microgrids är en bottom-up ansats för produktion ochintegrering av förnybar energi.Energiförsörjning av flera sammankoppladeMicrogrids studeras in detta arbete genommodellbaserad prediktiv kontroll (MPC). Ett optimeringsproblem formuleras på de enskildaenheterna med Alternating DirectionMethod ofMultipliers (ADMM) och parallellberäkningar härledas.Microgrids samarbetar för att nå en global lösning av neighbourto-neighbour kommunikation.Distribuerad energiförsörjning av microgrids analyseras och två kontroll algorithmerutformas.

Opportunistic spectrum access has become a high priority research area in the past few years. The motivation behind this actively researched area is the fact that the limited spectrum available is currently being utilized in an inefficient way. The complete wireless spectrum is assigned and reserved, but not necessarily being used. At the same time, the demand for innovation in wireless technology is growing. Since there is no room in the wireless spectrum to allocate significant frequency bands for future wireless technologies, the only recourse is to increase utilization of the spectrum. To achieve this, we must find a way to share the spectrum. Spectrum sharing techniques will require coordination between all the layers of the protocol stack. The network and the wireless medium are inextricably linked and, thus, both must be considered when optimizing wireless network performance. Unfortunately, interactions in the wireless medium can lead to non-convex problems which have been shown to be NP-hard. Techniques must be developed to tackle the optimization problems that arise from wireless network analysis. In this document we focus on analyzing the spectrum sharing problem from two perspectives: cooperative game theory and non-convex optimization. We develop a cooperative game theory model to analyze a scenario where nodes in a multi-hop wireless network need to agree on a fair allocation of spectrum. We show that in high interference environments, the utility space of the game is non-convex, which may make some optimal allocations unachievable with pure strategies. However, we show that as the number of channels available increases, the utility space becomes close to convex and thus optimal allocations become achievable with pure strategies. We propose the use of the NBS and show that it achieves a good compromise between fairness and efficiency, using a small number of channels. We also propose a distributed algorithm for spectrum sharing and show that it achieves allocations reasonably close to the NBS. In our game theory analysis, we studied the possible outcomes of the spectrum sharing problem and propose the NBS as a desirable outcome and propose an algorithm to achieve the NBS spectrum allocation. However, the expression used to compute the NBS is a non-convex optimization problem. We propose an optimization model to solve a class of problems that incorporate the non-convex dynamics of the wireless medium that occur when the objective is a function of SINR. We present two case studies to show the application of the model to discrete and continuous optimization problems. We propose a branch and bound heuristic, based on the RLT, for approximating the solution of continuous optimization problems. Finally, we present results for the continuous case study. We show simulation results for the heuristic compared to a time constrained mixed integer linear program (MILP) as well as a nonlinear optimization using random starting points. We show that for small networks the MILP achieves the optimal in reasonable time and the heuristic achieves a value close to the optimal. We also show that for large networks the heuristic outperforms the MILP as well as the nonlinear search.
Ph. D.

This dissertation focuses on the study of decentralized coordination algorithms of multiple autonomous vehicles. Here, the term decentralized coordination is used to refer to the behavior that a group of vehicles reaches the desired group behavior via local interaction. Research is conducted towards designing and analyzing distributed coordination algorithms to achieve desired group behavior in the presence of none, one, and multiple group reference states. Decentralized coordination in the absence of any group reference state is a very active research topic in the systems and controls society. We first focus on studying decentralized coordination problems for both single-integrator kinematics and double-integrator dynamics in a sampled-data setting because real systems are more appropriate to be modeled in a sampled-data setting rather than a continuous setting. Two sampled-data consensus algorithms are proposed and the conditions to guarantee consensus are presented for both fixed and switching network topologies. Because a number of coordination algorithms can be employed to guarantee coordination, it is important to study the optimal coordination problems. We further study the optimal consensus problems in both continuous-time and discrete-time settings via an linear-quadratic regulator (LQR)-based approach. Noting that fractional-order dynamics can better represent the dynamics of certain systems, especially when the systems evolve under complicated environment, the existing integer-order coordination algorithms are extended to the fractional-order case. Decentralized coordination in the presence of one group reference state is also called coordinated tracking, including both consensus tracking and swarm tracking. Consensus tracking refers to the behavior that the followers track the group reference state. Swarm tracking refers to the behavior that the followers move cohesively with the external leader while avoiding inter-vehicle collisions. In this part, consensus tracking is studied in both discrete-time setting and continuous-time settings while swarm tracking is studied in a continuous-time setting. Decentralized coordination in the presence of multiple group reference states is also called containment control, where the followers will converge to the convex hull, i.e., the minimal geometric space, formed by the group references states via local interaction. In this part, the containment control problem is studied for both single-integrator kinematics and double-integrator dynamics. In addition, experimental results are provided to validate some theoretical results.

Une structure de contrôle distribué partiellement coopérative est proposée dans cette thèse. La structure est consacrée au problème de commande d’un réseau composé de sous-systèmes non linéaires/linéaires qui sont interconnectés par leurs états et les entrées de commande. Par la coopération partielle, cela signifie que chaque sous-système est capable de préserver son propre objectif en utilisant un indice de la coopération ajustable qui définit dans quelle mesure il accepte de dégrader son propre niveau de performance afin d’aider ses voisins à maintenir leur intégrité sous les interconnexions potentiellement déstabilisantes. La communication entre les sous-systèmes est basée sur l’échange de niveaux de fonction de Lyapunov avec les contraintes associées et la quantité d’information transmise est plutôt réduite par rapport aux travaux les plus récents. Une autre caractéristique intéressante de cet structure de contrôle distribué non linéaire coopératif est l’utilisation de vecteurs prioritaires par chaque sous-système. Ce vecteur définit un ordre hiérarchique de l’importance de ses voisins menant à une stratégie de coopération dans lequel les sous-systèmes critiques dans le réseau peuvent être préservés en dépit des interactions. Une version linéaire de la structure de contrôle distribué coopératif est présenté. Cette conception de structure linéaire conduit à une évaluation rigoureuse de stabilité du réseau en boucle fermée globale. Une méthode d’amélioration de la stabilité est proposée basée sur la résolution d’un problème d’optimisation non convexe avec des degrés de liberté liés au paramétrage de l’affectation de priorité. Pour montrer son efficacité, le contrôle distribué coopératif proposé pour le réseau linéaire est appliqué pour traiter le problème de contrôle de la fréquence de charge dans un réseau d’alimentation et le problème de contrôle du système cryogénique
In this dissertation, a partially cooperative distributed control framework is proposed. The framework is dedicated to the control problem for a network consisting of linear/nonlinear subsystems that are interconnected through their states and control inputs. By partial cooperation, it means that each subsystem is able to preserve its own objective while using a tunable cooperation index that defines to what extend it accepts to degrade its own performance level so as to help its neighbors maintain their integrity under potentially destabilizing interconnections. The communication between the subsystems is rather reduced comparing to most of the existing contributions. Another attractive feature of the proposed framework is that each subsystem in the network can be assigned with priority indicating the importance of the corresponding subsystem seen by its neighbors. Through proper parameterization of the priority assignment, improved performance of the subsystems and the network can be acheived. In the linear version, a rigorous stability assessment method is presented and a systematic way of proposing an optimized priority assignment for a given network is introduced as well. The proposed scheme is applied to handle the load frequency control problem in a 4-area power network and the control problem of a cryogenic system to illustrate its effectiveness

In preparation for the influx of renewable energy sources that will be added to the electrical system, flexible and adaptable control schemes are necessary to accommodate the changing infrastructure. Microgrids have been gaining much attention as the main solution to the challenges of distributed and intermittent generation, but due to their low inertia, they need fast-acting control systems in order to maintain stability. Multi-Agent Systems have been proposed as dynamic control and communication frameworks. Decentralized arrangements of agents can provide resiliency and the much-desired “plug and play” behavior. This thesis describes a control system that implements droop control and the diffusion communication scheme without the need of a centralized controller to coordinate the Microgrid agents to maintain the frequency and stable operating conditions of the system. Moreover, the inter-agent communication is unaffected by changing network configurations and can achieve optimal economic dispatch through distributed optimization.

L'utilisation d'équipes de robots a pris de l'ampleur ces dernières années. Cela est dû aux avantages que peut offrir une équipe de robot par rapport à un robot seul pour la réalisation d'une même tâche. Cela s'explique aussi par le fait que ce type de plates-formes deviennent de plus en plus abordables et fiables. Ainsi, l'utilisation d'une équipe de véhicules aériens devient une alternative viable. Cette thèse se concentre sur le problème du déploiement d'une équipe de Micro-Véhicules Aériens (MAV) pour effectuer des missions de surveillance sur un terrain inconnu de morphologie arbitraire. Puisque la morphologie du terrain est inconnue et peut être complexe et non-convexe, les algorithmes standards ne sont pas applicables au problème particulier traité dans cette thèse. Pour y remédier, une nouvelle approche basée sur un algorithme d'optimisation cognitive et adaptatif (CAO) est proposée et évaluée. Une propriété fondamentale de cette approche est qu'elle partage les mêmes caractéristiques de convergence que les algorithmes de descente de gradient avec contraintes qui exigent une connaissance parfaite de la morphologie du terrain pour optimiser la couverture. Il est également proposé une formulation différente du problème afin d'obtenir une solution distribuée, ce qui nous permet de surmonter les inconvénients d'une approche centralisée et d'envisager également des capacités de communication limitées. De rigoureux arguments mathématiques et des simulations étendues établissent que l'approche proposée fournit une méthodologie évolutive et efficace qui intègre toutes les contraintes physiques particulières et est capable de guider les robots vers un arrangement qui optimise localement la surveillance. Finalement, la méthode proposée est mise en œuvre sur une équipe de MAV réels pour réaliser la surveillance d'un environnement extérieur complexe.

La recherche et le suivi de cibles mobiles constituent une tâche d'intérêt mais notablement difficile parmi les diverses applications des robots. Cette thèse considère la recherche et le suivi d'un nombre inconnu de cibles mobiles se déplaçant dans une zone délimitée par une flotte coopérative de véhicules aériens sans pilote (UAV). Des schémas d'estimation et de contrôle distribués sont présentés. Les schémas d'estimation reposent sur l'hypothèse que les perturbations d'état et les bruits de mesure sont bornés. Des estimateurs distribués robustes ensemblistes sont utilisés pour caractériser l'ensemble garanti de contenir les cibles. Les estimations ensemblistes sont mises à jour par chaque drone à l'aide des informations recueillies par ses propres capteurs et par les drones voisins. Les trajectoires des UAVs sont calculées en utilisant des approches de contrôle prédictif de modèle. Les lois de commande sont conçues afin de diminuer l'incertitude d'estimation des cibles inconnues, non encore détectées, et des cibles déjà connues et faisant l'objet d'un suivi. Les schémas d'estimation et de contrôle développés reposent sur de nouveaux modèles détaillés de conditions déterministes d'identification et de détection des cibles. Ces conditions tiennent compte des états du drone et de la cible, des contraintes des capteurs et des obstacles environnementaux. Les estimateurs développés utilisent des mesures de cibles identifiées et non identifiées et sont robustes à la présence de leurres potentiels, qui peuvent être confondus avec les cibles. En outre, le nouveau modèle de détection déterministe permet d'évaluer des estimations ensemblistes garanties de l'emplacement des cibles dans des environnements structurés inconnus, où il est difficile de démontrer l'absence d'une cible à une localisation donnée. Pour effectuer cette estimation, il n'est pas nécessaire de disposer d'une carte de l'environnement ou de la construire. Diverses simulations illustrent la capacité des approches proposées à rechercher et à suivre efficacement un nombre inconnu de cibles mobiles dans une zone de recherche délimitée. De plus, les résultats obtenus par de premières expérimentations sont présentés
Searching and tracking mobile targets remains a challenging task among the various applications for robots. This thesis considers the search and track of an unknown number of targets moving in a bounded area by a cooperative Unmanned Aerial Vehicle (UAV) fleet. Distributed estimation and control schemes are presented. The estimation schemes rely on the assumption that state perturbations and measurement noises are bounded. Robust distributed set-membership estimators are used to evaluate set estimates that are guaranteed to contain the target states. The set estimates are updated by each UAV using information collected from its sensors and from the neighboring UAVs. The trajectories of the UAVs are designed using model predictive control approaches. The control is designed to decrease the estimation uncertainty of the unknown, not yet detected targets and known, tracked targets.The developed estimation and control schemes rely on new detailed models of deterministic identification and detection conditions of the targets. These conditions account for UAV and target states, sensor constraints, and environmental obstacles. The developed estimators utilize measurements of identified and unidentified targets and are robust to the presence of potential decoys, which may be confused with the targets. Furthermore, the new deterministic detection model allows the evaluation of guaranteed set estimates of target locations in unknown structured environments, where it is challenging to demonstrate the absence of a target at a given location. To estimate the target locations, neither having nor building a map of the environment is necessary.Various simulations illustrate the ability of the proposed approaches to efficiently search and track an unknown number of moving targets within some delimited search area. Additionally, preliminary experimental studies are carried out

This thesis is devoted to design Model Predictive Control (MPC) strategies aiming to enhance the management of constrained generalised flow-based networks, with special attention to the economic optimisation and robust performance of such systems. Several control schemes are developed in this thesis to exploit the available economic information of the system operation and the disturbance information obtained from measurements and forecasting models. Dynamic network flows theory is used to develop control-oriented models that serve to design MPC controllers specialised for flow networks with additive disturbances and periodically time-varying dynamics and costs. The control strategies developed in this thesis can be classified in two categories: centralised MPC strategies and non-centralised MPC strategies. Such strategies are assessed through simulations of a real case study: the Barcelona drinking water network (DWN). Regarding the centralised strategies, different economic MPC formulations are first studied to guarantee recursive feasibility and stability under nominal periodic flow demands and possibly time-varying economic parameters and multi-objective cost functions. Additionally, reliability-based MPC, chance-constrained MPC and tree-based MPC strategies are proposed to address the reliability of both the flow storage and the flow transportation tasks in the network. Such strategies allow to satisfy a customer service level under future flow demand uncertainty and to efficiently distribute overall control effort under the presence of actuators degradation. Moreover, soft-control techniques such as artificial neural networks and fuzzy logic are used to incorporate self-tuning capabilities to an economic certainty-equivalent MPC controller. Since there are objections to the use of centralised controllers in large-scale networks, two non-centralised strategies are also proposed. First, a multi-layer distributed economic MPC strategy of low computational complexity is designed with a control topology structured in two layers. In a lower layer, a set of local MPC agents are in charge of controlling partitions of the overall network by exchanging limited information on shared resources and solving their local problems in a hierarchical-like fashion. Moreover, to counteract the loss of global economic information due to the decomposition of the overall control task, a coordination layer is designed to influence non-iteratively the decision of local controllers towards the improvement of the overall economic performance. Finally, a cooperative distributed economic MPC formulation based on a periodic terminal cost/region is proposed. Such strategy guarantees convergence to a Nash equilibrium without the need of a coordinator and relies on an iterative and global communication of local controllers, which optimise in parallel their control actions but using a centralised model of the network.
Esta tesis se enfoca en el diseño de estrategias de control predictivo basado en modelos (MPC, por sus siglas en inglés) con la meta de mejorar la gestión de sistemas que pueden ser descritos por redes generalizadas de flujo y que están sujetos a restricciones, enfatizando especialmente en la optimización económica y el desempeño robusto de tales sistemas. De esta manera, varios esquemas de control se desarrollan en esta tesis para explotar tanto la información económica disponible de la operación del sistema como la información de perturbaciones obtenida de datos medibles y de modelos de predicción. La teoría de redes dinámicas de flujo es utilizada en esta tesis para desarrollar modelos orientados a control que sirven para diseñar controladores MPC especializados para la gestión de redes de flujo que presentan tanto perturbaciones aditivas como dinámicas y costos periódicamente variables en el tiempo. Las estrategias de control propuestas en esta tesis se pueden clasificar en dos categorías: estrategias de control MPC centralizado y estrategias de control MPC no-centralizado. Dichas estrategias son evaluadas mediante simulaciones de un caso de estudio real: la red de transporte de agua potable de Barcelona en España. En cuanto a las estrategias de control MPC centralizado, diferentes formulaciones de controladores MPC económicos son primero estudiadas para garantizar factibilidad recursiva y estabilidad del sistema cuya operación responde a demandas nominales de flujo periódico, a parámetros económicos posiblemente variantes en el tiempo y a funciones de costo multi-objetivo. Adicionalmente, estrategias de control MPC basado en fiabilidad, MPC con restricciones probabilísticas y MPC basado en árboles de escenarios son propuestas para garantizar la fiabilidad tanto de tareas de almacenamiento como de transporte de flujo en la red. Tales estrategias permiten satisfacer un nivel de servicio al cliente bajo incertidumbre en la demanda futura, así como distribuir eficientemente el esfuerzo global de control bajo la presencia de degradación en los actuadores del sistema. Por otra parte, técnicas de computación suave como redes neuronales artificiales y lógica difusa se utilizan para incorporar capacidades de auto-sintonía en un controlador MPC económico de certeza-equivalente. Dado que hay objeciones al uso de control centralizado en redes de gran escala, dos estrategias de control no-centralizado son propuestas en esta tesis. Primero, un controlador MPC económico distribuido de baja complejidad computacional es diseñado con una topología estructurada en dos capas. En una capa inferior, un conjunto de controladores MPC locales se encargan de controlar particiones de la red mediante el intercambio de información limitada de los recursos físicos compartidos y resolviendo sus problemas locales de optimización de forma similar a una secuencia jerárquica de solución. Para contrarrestar la pérdida de información económica global que ocurra tras la descomposición de la tarea de control global, una capa de coordinación es diseñada para influenciar no-iterativamente la decisión de los controles locales con el fin de lograr una mejora global del desempeño económico. La segunda estrategia no-centralizada propuesta en esta tesis es una formulación de control MPC económico distribuido cooperativo basado en una restricción terminal periódica. Tal estrategia garantiza convergencia a un equilibrio de Nash sin la necesidad de una capa de coordinación pero requiere una comunicación iterativa de información global entre todos los controladores locales, los cuales optimizan en paralelo sus acciones de control utilizando un modelo centralizado de la red.

Cette thèse développe les lois de coordination de systèmes de Lagrange. Elle propose en premier lieu une stratégie complètement décentralisée qui se base sur la technique de cross-coupling pour la commande d'un groupe de robots, appelé réseau, qui synchronisent leurs mouvements en suivant une trajectoire désirée. Cette stratégie est étendue pour faire face à l'incertitude paramétrique des robots ainsi qu’aux retards fréquemment rencontrés dans les applications pratiques de réseaux de communication. Une deuxième architecture basée sur la théorie des graphes est proposée pour les réseaux à leader. L'approche développée est considérée hybride. Une extension adaptative à base de réseaux de neurones est développée pour traiter les cas d'incertitude paramétrique. La stratégie conçue prend en considération les délais dans la réception des données. En se basant sur la notion de système en chaîne, la théorie des graphes, le concept de la passivité et la technique du backstepping, une nouvelle méthodologie de la conception de contrôleur de synchronisation pour une classe de systèmes sous-actionnés est développée. Afin d’avoir la possibilité d’implémenter ces stratégies de contrôle, on a développé une plate-forme d'expérimentation pour la robotique industrielle coopérative
This thesis investigates the issue of designing decentralized control laws to cooperatively control a team of robot manipulators. The purpose is to synchronize their movements while tracking common desired trajectory. Based on a combination of Lyapunov direct method and cross-coupling technique, To account for unmatched uncertainties, the proposed decentralized control laws are extended to an adaptive synchronization tracking controllers. Moreover, due to communication imperfection, time delay communication problems are considered in the performance analysis of the controllers. Another relevant problem for distributed synchronized systems is the leader-follower control problem. In this strategy, a decentralized control laws based on the backstepping scheme is proposed to deal with a leader-follower multiple robots structure. Based on graph theory, the coordination strategy combines the leader follower control with the decentralized control. The thesis, also considers the cooperative movement of under- actuated manipulators tracking reference trajectories defined by the user. The control problem for a network of class of under-actuated systems is considered. The approach we adopted in this thesis consists in decomposing the under-actuated manipulators into a cascade of passive subsystems that synchronize with he other neighbors subsystems. The resulting synchronized control law is basically a combination of non-regular backstepping procedure aided with some concepts from graph theory. The proposed controllers are validated numerically, assuming that the underlying communication graph is strongly connected. To implement these control strategies, we developed an experimental platform made of three robot manipulators

This thesis is mainly devoted to the study of the role of evolutionary-game theory in the design of distributed optimization-based controllers. Game theoretical approaches have been used in several engineering fields, e.g., drainage wastewater systems, bandwidth allocation, wireless networks, cyber security, congestion games, wind turbines, temperature control, among others. On the other hand, a specific class of games, known as population games, have been mainly used in the design of controllers to manage a limited resource. This game approach is suitable for resource allocation problems since, under the framework of full-potential games, the population games can satisfy a unique coupled constraint while maximizing a potential function. First, this thesis discusses how the classical approach of the population games can contribute and complement the design of optimization-based controllers. Therefore, this dissertation assigns special interest on how the features of the population-game approach can be exploited extending their capabilities in the solution of distributed optimization problems. In addition, density games are studied in order to consider multiple coupled constraints and preserving the non-centralized information requirements. Furthermore, it is established a close relationship between the possible interactions among agents in a population with the constrained information sharing among different local controllers. On the other hand, coalitional games are discussed focusing on the Shapley power index. This power index has been used to assign an appropriate rewarding to players in function of their contributions to all possible coalitions. Even though this power index is quite useful in the engineering context, since it involves notions of fairness and/or relevance (how important players are), the main difficulty of the implementation of the Shapley value in engineering applications is related to the high computational burden. Therefore, this dissertation studies the Shapley value in order to propose an alternative manner to compute it reducing computational time, and a different way to find it by using distributed communication structures is presented. The studied game theoretical approaches are suitable for the modeling of rational agents involved in a strategic constrained interaction, following local rules and making local decisions in order to achieve a global objective. Making an analogy, distributed optimization-based controllers are composed of local controllers that compute optimal inputs based on local information (constrained interactions with other local controllers) in order to achieve a global control objective. In addition to this analogy, the features that relate the Nash equilibrium with the Karush-Kuhn-Tucker conditions for a constrained optimization problem are exploited for the design of optimization-based controllers, more specifically, for the design of model predictive controller. Moreover, the design of non-centralized controllers is directly related to the partitioning of a system, i.e., it is necessary to represent the whole system as the composition of multiple sub-systems. This task is not a trivial procedure since several considerations should be taken into account, e.g., availability of information, dynamical coupling in the system, regularity in the amount of variables for each sub-system, among others. Then, this doctoral dissertation also discusses the partitioning problem for large-scale systems and the role that this procedure plays in the design of distributed optimization-based controllers. Finally, dynamical partitioning strategies are presented with distributed population-games-based controllers. Some engineering applications are presented to illustrate and test the performance of all the proposed control strategies, e.g., the Barcelona water supply network, multiple continuous stirred tank reactors, system of multiple unmanned aerial vehicles.
Esta tesis doctoral consiste principalmente en el estudio del rol que desempeña la teoría de juegos evolutiva en el diseño de controladores distribuidos basados en optimización. Diversos enfoques de la teoría de juegos han sido usados en múltiples campos de la ingeniera, por ejemplo, en sistemas de drenaje urbano, para la asignación de anchos de banda, en redes inalámbricas, en ciber-seguridad, en juegos de congestión, turbinas eólicas, control de temperatura, entre otros. Por otra parte, una clase especifica de juegos, conocidos como juegos poblacionales, se han usado principalmente en el diseño de controladores encargados de determinar la apropiada asignación de recursos. Esta clase de juegos es apropiada para problemas de distribución dinámica de recursos dado que, en el contexto de juegos poblacionales, los juegos poblacionales pueden ser usados para maximizar una función potencial mientras se satisface una restricción acoplada. Primero, esta tesis doctoral presenta como el enfoque clásico de los juegos poblacionales pueden contribuir y complementar en el diseño de controladores basados en optimización. Posteriormente, esta disertación concentra su atención en cómo las características de los juegos poblacionales pueden ser aprovechadas y extendidas para dar solución a problemas de optimización de forma distribuida. Adicionalmente, los juegos con dependencia de densidad son estudiados con el fin de considerar múltiples restricciones mientras se preservan las características no centralizadas de los requerimientos de información. Finalmente, se establece una estrecha relación entre las posibles interacciones de los agentes en una población y las restricciones de intercambio de información entre diversos controladores locales. También, se desarrolla una discusión sobre los juegos cooperativos y el índice de poder conocido como el valor de Shapley. Este índice de poder ha sido usado para la apropiada asignación de beneficios para un jugador en función de sus contribuciones a todas las posibles coaliciones que pueden formarse. Aunque este índice de poder es de gran utilidad en el contexto ingenieril, ya que involucra nociones de justicia y/o relevancia, la principal dificultad para implementar el valor de Shapley en aplicaciones de ingeniería está asociado a los altos costos computacionales para encontrarlo. En consecuencia, esta disertación doctoral estudia el valor de Shapley con el fin de ofrecer una alternativa para calcular este índice de poder reduciendo los costos computacionales e incluso contemplando estructuras distribuidas de comunicación. Los enfoques de la teoría de juegos estudiados son apropiados para el modelamiento de agentes racionales involucrados en una interacción estratégica con restricciones, siguiendo reglas locales y tomando decisiones locales para alcanzar un objetivo global. Realizando una analogía, los controladores distribuidos basados en optimización están compuestos por controladores locales que calculan acciones óptimas basados en información local (considerando interacciones restringidas con otros controladores locales) con el fin de alcanzar un objetivo global. Adicional a esta analogía, las características que relacionan el equilibrio de Nash con las condiciones de Karush-Kuhn-Tucker en un problema de optimizaciones con restricciones son aprovechadas para el diseño de controladores basados en optimización, más específicamente, para el diseño de controladores predictivos. Por otra parte, el diseño de controladores no centralizados está directamente relacionado con el particionado de un sistema, es decir, es necesario representar el sistema en su totalidad por medio del conjunto de varios sub-sistemas. Esta tarea no es un procedimiento trivial puesto que es necesario tener en cuenta varias consideraciones, por ejemplo, la disponibilidad de información, el acople dinámico en el sistema, la regularidad en cuanto a la cantidad de variables en cada sub-sistema, entre otras. Por lo tanto, esta disertación doctoral también desarrolla una discusión alrededor del problema de particionado para sistemas de gran escala y respecto al rol que este procedimiento de particionado juega en el diseño de controladores distribuidos basados en optimización. Finalmente, se presentan estrategias de particionado dinámico junto con controladores basados en juegos poblacionales. Algunas aplicaciones en ingeniería son usadas para ilustrar y probar los controladores diseñados por medio de las contribuciones novedosas basadas en teoría de juegos, estas son, la red de agua potable de Barcelona, múltiples reactores, sistema compuesto por varios vehículos aéreos no tripulados y un sistema de distribución de agua.
Aquesta tesi doctoral consisteix principalment en l'estudi del paper que exerceix la teoria de jocs evolutiva en el disseny de controladors distribuïts basats en optimització. Diversos enfocaments de la teoria de jocs han estat usats en múltiples camps de l'enginyeria, per exemple, en sistemes de drenatge urbà, per a l’assignació d'amples de banda, en xarxes sense fils, a ciber-seguretat, en jocs de congestió, turbines eòliques, control de temperatura, entre altres. D'altra banda, una classe especifica de jocs, coneguts com jocs poblacionals, s'han fet servir principalment en el disseny de controladors encarregats de determinar l'apropiada assignació de recursos. Aquesta classe de jocs és apropiada per a problemes de distribució dinàmica de recursos atès que, en el context de jocs poblacionals, aquests poden ser usats per a maximitzar una funció potencial mentre es satisfà una restricció acoblada. Primer, aquesta tesi doctoral presenta com l'enfocament clàssic dels jocs poblacionals poden contribuir i complementar en el disseny de controladors basats en optimització. Posteriorment, aquesta dissertació concentra la seva atenció en com les característiques dels jocs poblacionals poden ser aprofitades i esteses per donar solució a problemes d’optimització de forma distribuïda. Addicionalment, els jocs amb dependència de densitat són estudiats amb la _finalitat de considerar múltiples restriccions mentre es preserven les característiques no centralitzades dels requeriments d’informació. Finalment, s'estableix una estreta relació entre les possibles interaccions dels agents en una població i les restriccions d'intercanvi d’informació entre diversos controladors locals. També, es desenvolupa una discussió sobre els jocs cooperatius i l’índex de poder conegut com el valor de Shapley. Aquest índex de poder ha estat usat per l'apropiada assignació de beneficis per a un jugador en funció de les seves contribucions a totes les possibles coalicions que poden formar-se. Encara que aquest índex de poder es de gran utilitat en el context de l'enginyeria, ja que involucra nocions de justícia i/o rellevància, la principal dificultat per implementar el valor de Shapley en aplicacions d'enginyeria està associat als alts costos computacionals per trobar-lo. En conseqüència, aquesta dissertació doctoral estudia el valor de Shapley per tal d'oferir una alternativa per calcular aquest índex de poder reduint els costos computacionals i fins i tot contemplant estructures distribuïdes de comunicació. Els enfocaments de la teoria de jocs estudiats són apropiats per al modelatge d'agents racionals involucrats en una interacció estratègica amb restriccions, seguint regles locals i prenent decisions locals per assolir un objectiu global. Realitzant una analogia, els controladors distribuïts basats en optimització estan compostos per controladors locals que calculen accions optimes basats en informació local (considerant interaccions restringides amb altres controladors locals) per tal d'assolir un objectiu global. Addicional a aquesta analogia, les característiques que relacionen l'equilibri de Nash amb les condicions de Karush-Kuhn-Tucker en un problema d’optimització amb restriccions són aprofitades per al disseny de controladors basats en optimització, més específicament, per al disseny de controladors predictius. D'altra banda, el disseny de controladors no centralitzats està directament relacionat amb la partició d'un sistema, és a dir, cal representar el sistema en la seva totalitat per mitjà del conjunt de diversos sub-sistemes. Aquesta tasca no és un procés trivial, ja que cal tenir en compte diverses consideracions, per exemple, la disponibilitat d’informació, l'acoblament dinàmic en el sistema, i la regularitat pel que fa a la quantitat de variables en cada sub-sistema, entre d'altres. Per tant, aquesta dissertació doctoral també desenvolupa una discussió al voltant del problema de partició per a sistemes de gran escala i respecte al paper que aquest procediment de partició juga en el disseny de controladors distribuïts basats en optimització. Finalment, es presenten estratègies de partició dinàmic juntament amb controladors basats en jocs poblacionals. Algunes aplicacions en enginyeria són usades per il·lustrar i provar els controladors dissenyats per mitjà de les contribucions noves basades en teoria de jocs, aquestes són: la xarxa d'aigua potable de Barcelona, múltiples reactors, sistema compost per diversos vehicles aeris no tripulats i un sistema de distribució d'aigua.

L'objectif de cette thèse est de définir puis d'étudier les performances de méthodes de guidage coopératif de véhicules aériens autonomes. L'intérêt du guidage coopératif est de confier une mission complexe à une flotte, plutôt qu'à un véhicule unique, afin de distribuer la charge de travail et d'améliorer les performances et la fiabilité. Les lois de guidage étudiées sont distribuées sur l'ensemble des véhicules afin d'une part, de répartir la charge de calcul et d'autre part, d'augmenter la fiabilité en éliminant la possibilité de perte de l'organe central de calcul de la commande.La première partie de la thèse porte sur les possibilités offertes par la règle des plus proches voisins. La loi de guidage développée consiste à ce que la commande de chaque véhicule soit élaborée en combinant les états des véhicules voisins. Afin de transmettre des consignes au groupe de véhicules, des objets dénommés agents virtuels sont introduits. Ceux-ci permettent de représenter des obstacles, d'indiquer une direction ou une cible au groupe de véhicules en utilisant des mécanismes déjà présent dans la loi de guidage.La seconde partie de la thèse porte sur les possibilités offertes par la commande prédictive. Ce type de commande consiste à employer un modèle du comportement du système afin de prédire les effets de la commande, et ainsi de déterminer celle qui minimise un critère de coût en respectant les contraintes du système. La loi de guidage développée emploi un critère de coût tenant compte et arbitrant entre les différents aspects de la mission (sécurité, progression de la mission, modération de la commande), et une procédure de recherche de la commande utilisant jeu prédéfinis de commandes candidates afin d'explorer l'espace de commande de manière efficace. Cette procédure, distincte des algorithmes d'optimisation habituels, génère une charge de calcul faible et constante, ne nécessite pas d'étape d'initialisation et est très peu sensible aux minima locaux.

The ability to gather and process information regarding the condition of forest fires is essential to cost-effective, safe, and efficient fire fighting. Advances in sensory and autopilot technology have made miniature unmanned aerial systems (UASs) an important tool in the acquisition of information. This thesis addresses some of the challenges faced when employing UASs for forest-fire perimeter surveillance; namely, perimeter tracking, cooperative perimeter surveillance, and path planning. Solutions to the first two issues are presented and a method for understanding path planning within the context of a forest-fire environment is demonstrated. Both simulation and hardware results are provided for each solution.

Ao observar a situação atual, na qual atos de vandalismo e terrorismo tornaram-se frequentes e cada vez mais presentes ao redor do mundo, principalmente em grandes cidades, torna-se clara a necessidade de equipar as forças policiais com tecnologias de observação e monitoramento inteligentes, capazes de identificar e monitorar indivíduos potencialmente perigosos que possam estar infiltrados nas multidões. Ao mesmo tempo, com sua recente popularização, veículos aéreos não tripulados, também chamados VANTs e conhecidos popularmente como "drones", acabaram por tornar-se ferramentas baratas e eficientes para diversas aplicações, incluindo observação, fornecendo a seus utilizadores a capacidade de monitorar alvos, áreas, ou prédios de forma segura e quase imperceptível. Unindo estas duas tendências, este trabalho apresenta o desenvolvimento de um sistema multi-VANT para observção de alvos móveis em multidões, demonstrando a possibilidade de utilização de pequenos VANTs comerciais comuns para o monitoramento de grupos de pedestres. O principal objetivo de tal sistema é monitorar continuamente indivíduos de interesse em um grupo de pessoas, visitando cada um destes indivíduos alternadamente, de forma a manter um registro geral do estado de cada um deles Um sistema deste tipo poderia, por exemplo, ser utilizado por autoridades no controle de manifestações e outras atividades em que grandes grupos de pessoas estejam envolvidos, ajudando a polícia e outros órgãos a identificar indivíduos com comportamento suspeito ou agressivo mais rapidamente, evitando ou minimizando os efeitos de atitudes de vandalismo e de ataques terroristas. Com o intuíto de abordar tal problema da forma mais completa e adequada possível, esta tese apresenta a concepção e o desenvolvimento de um sistema híbrido composto de três diferentes algoritmos: um algoritmo de distribuição de alvos; um de roteamento; e um de repasse de alvos. Primeiramente, neste sistema, um algoritmo de distribuição de alvos baseado em um paradigma de mercado que simula um leilão distribui os alvos entre os VANTs da melhor forma possível. Os VANTs, por sua vez, utilizam um algoritmo genético de roteamento para resolver uma instância do Problema do Caixeiro Viajante e decidir a melhor rota para visitar cada alvo sob sua responsabilidade. Ao mesmo tempo, o sistema analisa a necessidade de redistribuição dos alvos, ativando um algoritmo capaz de realizar esta ação ao perceber sua necessidade quando na iminência de perder algum alvo de vista. Ao fim de seu desenvolvimento, o sistema proposto foi testado em uma série de experimentos especialmente desenvolvidos para avaliar seu desempenho em situações controladas e comprovar sua eficiência para realizar a missão pretendida.
Observing the current scenario, where terrorism and vandalism acts have become commonplace, particularly in big cities, it becomes clear the need to equip law enforcement forces with an efficient observation method, capable of identifying and observing potentially threatening individuals on crowds, to avoid or minimize damage in case of attacks. Moreover, with the popularization of small lightweight Unmanned Aerial Vehicles (UAVs), these have become an affordable and efficient tool, which can be used to track and follow targets or survey areas or buildings quietly, safely and almost undetectably. This work presents the development of a multi-UAV based crowd monitoring system, demonstrating a system that uses small Commercial Of The Shelf (COTS) UAVs to periodically monitor a group of moving walking individuals. The goal of this work is to develop a coordination system for a swarm of UAVS capable of continuously monitoring a large group of individuals (targets) in a crowd, alternately observing each of them at a time while trying to not lose sight of any of these targets. A system equipped with a group of UAVs running this proposal can be used for law-enforcement applications, assisting authorities to monitor crowds in order to identify and to follow suspicious individuals that can have attitudes that could be classified as vandalism or linked to terrorist attack attempts To address this problem a system composed of three parts is proposed and was developed in this thesis. First, an auction algorithm was put in place to distribute interest targets among the multiple UAVs. The UAVs, in turn, make use of a genetic algorithm to calculate the order in which they would visit each of the targets on their observation queue. Moreover, a target handover algorithm was also implemented to redistribute targets among the UAVs in case the system judged that a target was about to be lost by its current observer UAV. The proposed system was evaluated through a set of experiments set-up to verify and to demonstrate the system capabilities to perform such monitoring task, proving its efficiency. During these experiments, it is made clear that the system as a whole has a great potential to solve this kind of moving target monitoring problem that can be mapped to a Time Dependent Travel Salesman Problem (TDTSP), observing targets, and redistributing them among UAVs as necessary during the mission.

Ad hoc networks are emerging as a cost-effective, yet, powerful tool for communication. These systems, where networks can emerge and converge on-the-fly, are guided by the forward-looking goals of providing ubiquitous connectivity and constant access to information. Due to power and bandwidth constraints, the vulnerability of the wireless medium, and the multi-hop nature of ad hoc networks, these networks are becoming increasingly complex dynamic systems. Besides, modern radios are empowered to be reconfigurable, which harbors the temptation to exploit the system. To understand the implications of these issues, some of which pose significant challenges to efficient network design, we study topology control using game theory. We develop a game-theoretic framework of topology control that broadly captures the radio parameters, one or more of which can be tuned under the purview of topology control. In this dissertation, we consider two parameters, viz. transmit power and channel, and study the impact of controlling these on the emergent topologies. We first examine the impact of node selfishness on the network connectivity and energy efficiency under two levels of selfishness: (a) nodes cooperate and forward packets for one another, but selfishly minimize transmit power levels and; (b) nodes selectively forward packets and selfishly control transmit powers. In the former case, we characterize all the Nash Equilibria of the game and evaluate the energy efficiency of the induced topologies. We develop a better-response-based dynamic that guarantees convergence to the minimal maximum power topology. We extend our analysis to dynamic networks where nodes have limited knowledge about network connectivity, and examine the tradeoff between network performance and the cost of obtaining knowledge. Due to the high cost of maintaining knowledge in networks that are dynamic, mobility actually helps in information-constrained networks. In the latter case, nodes selfishly adapt their transmit powers to minimize their energy consumption, taking into account partial packet forwarding in the network. This work quantifies the energy efficiency gains obtained by cooperation and corroborates the need for incentivizing nodes to forward packets in decentralized, energy-limited networks. We then examine the impact of selfish behavior on spectral efficiency and interference minimization in multi-channel systems. We develop a distributed channel assignment algorithm to minimize the spectral footprint of a network while establishing an interference-free connected network. In spite of selfish channel selections, the network spectrum utilization is shown to be within 12% of the minimum on average. We then extend the analysis to dynamic networks where nodes have incomplete network state knowledge, and quantify the price of ignorance. Under the limitations on the number of available channels and radio interfaces, we analyze the channel assignment game with respect to interference minimization and network connectivity goals. By quantifying the interference in multi-channel networks, we illuminate the interference reduction that can be achieved by utilizing orthogonal channels and by distributing interference over multiple channels. In spite of the non-cooperative behavior of nodes, we observe that the selfish channel selection algorithm achieves load balancing. Distributing the network control to autonomous agents leaves open the possibility that nodes can act selfishly and the overall system is compromised. We advance the need for considering selfish behavior from the outset, during protocol design. To overcome the effects of selfishness, we show that the performance of a non-cooperative network can be enhanced by appropriately incentivizing selfish nodes.
Ph. D.

Cognitive radios have been proposed as a new technology to counteract the spectrum scarcity issue and increase the spectral efficiency. In cognitive radios, the sparse assigned frequency bands are opened to secondary users, provided that interference induced on the primary licensees is negligible. Cognitive radios are established in two steps: the radios firstly sense the available frequency bands by detecting the presence of primary users and secondly communicate using the bands that have been identified as not in use by the primary users.

In this thesis we investigate how to improve the efficiency of cognitive radio networks when multiple cognitive radios cooperate to sense the spectrum or control their interferences. A major challenge in the design of cooperating devices lays in the need for exchange of information between these devices. Therefore, in this thesis we identify three specific types of control information exchange whose efficiency can be improved. Specifically, we first study how cognitive radios can efficiently exchange sensing information with a coordinator node when the reporting channels are noisy. Then, we propose distributed learning algorithms allowing to allocate the primary network sensing times and the secondary transmission powers within the secondary network. Both distributed allocation algorithms minimize the need for information exchange compared to centralized allocation algorithms.
Doctorat en Sciences de l'ingénieur
info:eu-repo/semantics/nonPublished

碩士
國立成功大學
電機工程研究所
83
Recently,network techniques improvement have make cooperative problem solving system possible. Each node takes advantage of di- stributed blackboard system to regard as job coordination and in- formation sharing that is a important subject. A cooperative con- trol architecture in distriduted blackboard system is presented in this thesis. This system will help application system develo- per to achieve the aim of building application system quickly. In this paper,cooperative problem solving and control archit- ecture include problem specification base (PSB)、cability base (CB)、control blackboard and strategy manager. PSB respond probl- em initiation and decomposition. CB record capability of each kn- owledge source and what knowledge sources that each node has.In cooperative problem solving will be solved sufficiently by matc- hing PSB and CB. In control architecture,control blackboard responds schedule and control of problem solving. Strategy manager responds coord- ination of each event in the system. Network communication mana- ger reponds communucation of each node. Domain blackboard control manager (DBCM) responds access right of blackboard.Integration of each moduler will provide a convenient developing tool of distri- buted application system.

碩士
國立臺灣大學
電信工程學研究所
97
Transmission reliability is one of the most important issues in wireless communi- cations. Different techniques have been proposed to improve transmission reliability in both physical (PHY) and medium access control (MAC) layers. Inspired by the multi-input multi-output (MIMO) system, cooperative transmission was introduced to obtain diversity gain without the complexity of using multi-antenna radios. This additional gain, when being used properly, can improve transmission reliability or reduce power consumption. In cooperative transmission, neighbors of the source device, referred to as relays, forward the data frame received from the source device to the destination device. To enable such cooperation, devices including the source, the relays, and the destination must know (1) when to cooperate and (2) whom to cooperate with. To address these issues, MAC-layer signaling and coordination among the three parties are needed. In this thesis, we design a new medium access control (MAC) protocol that sup- ports cooperative transmission. The new protocol enables devices to adapt trans- mission schemes (direct or cooperative) to dynamic wireless environments. With our protocol, the devices exchange the link information and perform relay selection — via contention — in a fully distributed manner. In order to select the best relay, we also introduce a ”busy-tone” relay raking system. To further improve the performance, a cross-layer optimization technique, namely adaptive modulation, is integrated into our protocol. We performed mathematical analysis and conducted extensive simulation in Opnet Modeler to show the performance. The overall throughput improvement varies from 10% to 20% in low-SNR environments. The results show that our protocol is a feasible iisolution and delivers considerable improvement even when taking into account all signaling overheads.

A cooperative multi-agent system is a collection of interacting agents deployed in a mission space where each agent is allowed to control its local state so that the fleet of agents collectively optimizes a common global objective. While optimization problems associated with multi-agent systems intend to determine the fixed set of globally optimal agent states, control problems aim to obtain the set of globally optimal agent controls. Associated non-convexities in these problems result in multiple local optima. This dissertation explores systematic techniques that can be deployed to either escape or avoid poor local optima while in search of provably better (still local) optima. First, for multi-agent optimization problems with iterative gradient-based solutions, a distributed approach to escape local optima is proposed based on the concept of boosting functions. These functions temporarily transform gradient components at a local optimum into a set of boosted non-zero gradient components in a systematic manner so that it is more effective compared to the methods where gradient components are randomly perturbed. A novel variable step size adjustment scheme is also proposed to establish the convergence of this distributed boosting process. Developed boosting concepts are successfully applied to the class of coverage problems. Second, as a means of avoiding convergence to poor local optima in multi-agent optimization, the use of greedy algorithms in generating effective initial conditions is explored. Such greedy methods are computationally cheap and can often exploit submodularity properties of the problem to provide performance bound guarantees to the obtained solutions. For the class of submodular maximization problems, two new performance bounds are proposed and their effectiveness is illustrated using the class of coverage problems. Third, a class of multi-agent control problems termed Persistent Monitoring on Networks (PMN) is considered where a team of agents is traversing a set of nodes (targets) interconnected according to a network topology aiming to minimize a measure of overall node state. For this class of problems, a gradient-based parametric control solution developed in a prior work relies heavily on the initial selection of its `parameters' which often leads to poor local optima. To overcome this initialization challenge, the PMN system's asymptotic behavior is analyzed, and an off-line greedy algorithm is proposed to systematically generate an effective set of initial parameters. Finally, for the same class of PMN problems, a computationally efficient distributed on-line Event-Driven Receding Horizon Control (RHC) solution is proposed as an alternative. This RHC solution is parameter-free as it automatically optimizes its planning horizon length and gradient-free as it uses explicitly derived solutions for each RHC problem invoked at each agent upon each event of interest. Hence, unlike the gradient-based parametric control solutions, the proposed RHC solution does not force the agents to converge to one particular behavior that is likely to be a poor local optimum. Instead, it keeps the agents actively searching for the optimum behavior. In each of these four parts of the thesis, an interactive simulation platform is developed (and made available online) to generate extensive numerical examples that highlight the respective contributions made compared to the state of the art.

Safety concerns have been keeping autonomous vehicles off the roads for decades, although the main drivers for introducing some autonomy are to increase safety, reduce congestion, and greenhouse gas emissions. Safety is a vast topic that includes the safety of the system alone, known as string stability, and the safety of the system on public roads. This thesis provides experimental validation of the string stability of the Assume-Guarantee approach. This approach suggests that each agent models the interactions with neighbors as bounded disturbances while simultaneously self-imposing symmetric magnitude bounds. Two main controllers were tested in an indoor lab set-up: decentralized platooning and decentralized cooperative adaptive cruise controllers. First, we tested three versions of the platooning controller whose objective is to maintain a constant spacing. They differ in the assumptions and guarantees. We observed a robust performance with relaxed bounds and some violations as the bounds become tighter and tighter. Second, we modified and transformed the platoon model into cooperative adaptive cruise control (CACC). Unlike the platoon controller, the cooperative adaptive cruise controller keeps the time gap constant. Two experiments were conducted at different velocities to evaluate the limitation of the controller. The results show a stable and smooth performance.

This thesis explores a game-theoretical approach for underwater environmental monitoring applications. We first apply game-theoretical algorithm to multi-agent resource coverage problem in drifting environments. Furthermore, existing utility design and learning process of the algorithm are modified to fit specific constraints of underwater exploration/monitoring tasks. The revised approach can take the real scenario of underwater monitoring applications such as the effect of sea current, previous knowledge of the resource and occasional communications between agents into account, and adapt to them to reach better performance. As the motivation of this thesis is from real applications, in this work we emphasize highly on implementation phase. A ROS-Gazebo simulation environment was created for preparation of actual tests. The algorithms are implemented in simulating both the dynamics of vehicles and the environment. After that, a multi-agent underwater autonomous robotic system was developed for hardware test in real settings with local controllers to make their own decisions. These systems are used for testing above mentioned algorithms and future development of other underwater projects. After that, other works related to robotics during this thesis will be briefly mentioned, including contributions in MBZIRC robotics competition and distributed control of UAVs in an adversarial environment.

no
In cognitive radio cooperative communication (CR-CC) systems, the achievable data rate can be improved by increasing the transmission power. However, the increase in power consumption may cause the interference with primary users and reduce the network lifetime. Most previous work on CR-CC did not take into account the tradeoff between the achievable data rate and network lifetime. To fill this gap, this paper proposes an energy-efficient joint relay selection and power allocation scheme in which the state of a relay is characterized by the channel condition of all related links and its residual energy. The CR-CC system is formulated as a multi-armed restless bandit problem where the optimal policy is decided in a distributed way. The solution to the restless bandit formulation is obtained through a first-order relaxation method and a primal-dual priority-index heuristic, which can reduce dramatically the on-line computation and implementation complexity. According to the obtained index, each relay can determine whether to provide relaying or not and also can control the corresponding transmission power. Extensive simulation experiments are conducted to investigate the effectiveness of the proposed scheme. The results demonstrate that the power consumption is reduced significantly and the network lifetime is increased more than 40%.

This thesis addresses a number of issues present in the modern and future power distribution system where high penetration of distributed generation (DG) and smart sensors change the environment in which power flow must be managed. The shift in balance of power supply from the centralized to the distributed can lead to network constraint breaches such as voltage and frequency limits, fault ride through capability, system security, reliability and stability. Common regulation approaches may be inadequate in addressing these network regulation problems, leading to inefficient use of DG and unnecessary high voltage (HV) grid imports. Furthermore, the increase in intelligent Smart Grid components will lead to the transmission and processing of large volumes of data making the optimal control of a network a more challenging problem. Optimisation methods must take into consideration the increase and distributed nature of data, and account for data synchronization, latency, and privacy issues. However, if these challenges can be overcome, then the increase in the controllability and observability of smart grid components, such as distributed generators, storage and controllable demands, offers great potential for the improvement of network optimality and stability. In this thesis, a set of innovative distributed algorithms are presented that solve the optimal power flow problem of a distribution network featuring advanced nodal monitoring and control of DG, storage and loads. These algorithms exploit the network structure to produce iterative solutions to solve the global optimisation problem. They are carefully developed taking into account the realistic limitations where each node can only exchange information with adjacent neighbours but does not have sufficient information about the other nodes in a large scale system. Two partitioning strategies are considered which aim to improve the structure of the communication and control subsystem in order to better facilitate optimal control. The first strategy measures subnet optimality according to the minimisation of mismatch between DG power and local demand, therefore maximising DG utilisation, minimising line loss, and minimising HV grid imports. The second strategy is based on sets of strongly coupled buses, where the coupling of buses is characterised according to the potential for a change in power at one bus to impact the state estimation error at another, therefore improving solution optimality. Subsequently, a distributed predictive optimal control algorithm is proposed, through the method of approximate dynamic programming, that utilises a central coordinator to improve network state estimation and control sequence optimality. The centrally coordinated solution has the benefit of a near optimal solution without burdening controllers with the high dimensional state of the entire distribution network, but rather utilising only a summary of global information. Improvements to the centrally coordinated scheme are then developed through a fully distributed optimal power flow algorithm that requires no central coordination. The fully distributed approach maintains the reduced computational requirements of controllers but improves on the centrally coordinated configuration by restricting data communication to local neighbourhoods. Three variants of the distributed OPF solution are suggested for application to three distinct scenarios: Optimal DG control in a distribution network, DG optimal control in an islanded distribution network, and optimal power management in a home energy management system. These three approaches address significant issues associated with distributed control. An optimal solution to the global problem is achievable in each case, and iterations of the algorithm are shown to be stable and convergent through the use of an augmented Lagrange formulation. Global information necessary for a feasible solution is shared through the development of a new asynchronous consensus protocol, and a communication protocol is presented to enable instantiation, execution and conclusion of fully distributed optimisation sessions. For each studied approach, algorithms are carefully developed that concisely define the method of application. For each presented algorithm, a reasonable amount of computer simulation is applied to verify their applicability to a range of relevant scenarios. The simulations study the algorithms’ convergence and scalability, solutions’ optimality in a local sense, and solution feasibility. In each case the simulations successfully demonstrate the presented methods’ practicality for the studied scenarios.

Wireless sensor networks are battery operated computing and sensing devices that collaborate to achieve a common goal for a specific application. They are formed by a cluster of sensor nodes where each sensor node is composed of a single chip with embedded memory (microprocessor), a transceiver for transmission and reception (resulting in the most energy consumption), a sensor device for event detection and a power source to keep the node alive. Due to the environmental nature of their application, it is not feasible to change or charge the power source once a sensor node is deployed. The main design objective in WSNs (Wireless Sensor Networks) is to define effective and efficient strategies to conserve energy for the nodes in the network. With regard to the transceiver, the highest consumer of energy in a sensor node, the factors contributing to energy consumption in wireless sensor networks include idle listening, where nodes keep listening on the channel with no data to receive; ovehearing, where nodes hears or intercept data that is meant for a different node; and collision, which occurs at the sink node when it receives data from different nodes at the same time. These factors all arise during transmission or reception of data in the Transceiver module in wireless sensor networks. A MAC (Medium Access Control) protocol is one of the techniques that enables successful operation while minimizing the energy consumption in the network. Its task is to avoid collision, reduce overhearing and to reduce idle listening by properly managing the state of each node in the network. The aim, when designing a MAC protocol for WSNs is to achieve a balance amongst minimum energy consumption, minimum latency, maximum fault-tolerance and providing QoS (Quality of Service). To carefully achieve this balance, this dissertation has proposed, designed, simulated and analyzed a new cooperative MAC scheme with an overhearing avoidance technique with the aim of minimizing energy consumption by attempting to minimize the overhearing in the WSN. The new MAC protocol for WSNs supports the cooperative diversity and overhearing communications in order to reduce the effects of energy consumption thus increase the network lifetime, providing improved communication reliability and further mitigating the effects of multipath fading in WSNs. The MAC scheme in this work focuses on cooperation with overhearing avoidance and reducing transmissions in case of link failures in order to minimize energy consumption. The cooperative MAC scheme presented herein uses the standard IEEE 802.15.4 scheme as its base physical model. It introduces cooperation, overhearing avoidance, receiver based relay node selection and a Markov-based channel state estimation. The performance analysis of the developed Energy Efficient Distributed Receiver based MAC (E2DRCMAC) protocol for WSNs shows an improvement from the standard IEEE 802.15.4 MAC layer with regard to the energy consumption, throughput, reliability of message delivery, bit error rates, system capacity, packet delay, packet error rates, and packet delivery ratios.
M.Sc.Eng. University of KwaZulu-Natal, Durban 2013.

Tese de doutoramento em Engenharia Electrotécnica e de Computadores apresentada à Faculdade de Engenharia da Univ do Porto
This thesis addresses the problem of how to share efficiently information within a robotic system comprised of several mobile robots, which are programmed to exhibit cooperative behavior in the context of building volumetric maps of unknown environments. More specifically, it addresses the following issues: representing a probabilistic map and improving it through efficient exploration, based on information gain maximization; distributed control of teams of cooperative mobile robots, based on an information utility criteria; and coordinated exploration, aiming at avoiding redundant sensory information and robots' interference. Robots have been developed essentially to help or substitute humans in tasks which are either repetitive or dangerous. For many of these tasks, especially those that are intrinsically distributed and complex, a team of several cooperative mobile robots ─ a cooperative multi-robot system (MRS) ─ is required to either make viable the mission accomplishment or, at least, accomplish the mission with better performance than a single mobile robot. In spite of potential advantages related with space distribution, time distribution, complex problems decomposition, robustness, reliability and cost, a MRS requires that each robot maintains a sufficient and consistent level of awareness about the mission assigned to the team and about its teammates, in order to attain effective cooperation. The main challenge is that information is distributed and thus each robot has only partial and, sometimes, inconsistent knowledge about the environment. Sharing efficiently information via communication is thus crucial for robots' cooperation. Building maps is indeed a relevant robotics' application domain. Firstly, in many other application domains than building maps (e.g. search and rescue, surveillance, planetary exploration, etc.), a robot usually needs a map to support safe and efficient navigation based on a world model. Secondly, robots may substitute humans on building detailed models, such as: fastidious maps of indoor environments (e.g. buildings); maps of buried utilities (e.g.gas pipes, power or communication lines, etc.), in order to avoid getting too close to them in construction activities; or detailed maps of hazardous environments (e.g. abandoned underground mines, nuclear facilities, etc.), in order to support monitoring or maintenance procedures. The contributions of this thesis include a compact grid-based probabilistic representation model of a volumetric map, which allows to explicitly model uncertainty through the entropy concept. A frontier-based exploration method is also formulated using entropy, so that each robot uses its current map to select a new exploration viewpoint with maximum information gain. This probabilistic framework is used to devise a distributed architecture model for building volumetric maps with teams of cooperative mobile robots, whereby each robot is altruistically committed to share useful measurements with its teammates. The information sharing is based on the formal definition of a measure of information utility, developed upon the concepts of entropy and mutual information, whereby sensory data is as useful as it contributes to improve the robot's map. The distributed architecture is further refined with a mechanism to coordinate the exploration actions of different robots, thus improving the team's performance. The proposed methods were implemented in mobile robots, equipped with wireless communication and a stereo-vision system providing range measurements. These robots were used to carry out a set of experiments in a physical environment, which successfully validated the proposed framework and demonstrated the performance improvement yielded by the robots' cooperation. The results obtained with mobile robots were complemented with extensive computer simulations, which demonstrated those methods with varying team sizes.

Mini Unmanned Aerial Vehicles (MUAVs) werden immer beliebtere Forschungsplattformen. Vor allem in den letzten Jahren ziehen sie aufgrund ihrer Erschwinglichkeit und ihrer Flexibilität, die es erlaubt sie in fast allen Lebensbereichen einzusetzen, beträchtliche Aufmerksamkeit auf sich. MUAVs haben offensichtliche Vorteile gegenüber bemannten Plattformen einschließlich ihrer viel geringeren Herstellungs- und Betriebskosten, Risikovermeidung für den menschlichen Piloten, der Möglichkeit sicher niedrig und langsam fliegen zu können, und Realisierung von Operationen, die über die inhärenten Grenzen des menschlichen Körpers hinausgehen. Der Fortschritt in der Micro Electro-Mechanical System (MEMS) Technologie, Avionik und Miniaturisierung von Sensoren spielte auch eine bedeutende Rolle bei der Entwicklung der MUAVs. Diese Fluggeräte reichen von einfachem Spielzeug aus dem Elektrofachhandel bis zu hoch entwickelten, kommerziellen Plattformen, die die Durchführung neuer Aufgaben wie Offshore-Windkraftwerk Inspektionen, 3D-Modellierung von Gebäuden usw. erlauben. MUAVs sind auch umweltfreundlich, da sie weniger Luftverschmutzung und Lärm verursachen. Unbemannt ist daher unübertroffen. Aktuelle Forschung konzentriert sich auf die Möglichkeit mehrere kostengünstige Fluggeräte zusammen fliegen zu lassen, während die erforderliche relative räumliche Trennungen beibehalten wird. Dies ermöglicht es effizient Aufgaben zu erfüllen im Vergleich zu einem einzigen sehr teuren Fluggerät. Durch die Redundanz entfällt auch das Risiko des Scheiterns der Mission durch den Verlust eines einzigen Fluggeräts. Wertvolle Aufgaben, die kooperative Fluggeräte ausführen können, sind beispielsweise gemeinsame Lasttransporte, Such- und Rettungsmissionen, mobile Kommunikationsrelais, Sprühen von Pestiziden und Wetterbeobachtung. Obwohl die Realisierung von Flügen mit mehreren, gekoppelten UAVs komplex ist, rechtfertigen dennoch offensichtliche Vorteile diese mühsame und aufwändige Entwicklungsarbeit. Verteilte Steuerung von kooperierenden Einheiten ist ein multidisziplinäres Thema, das es erfordert in diversifizierten Bereichen zu arbeiten. Dazu gehören MUAV Hardware und Software, Kommunikationstechniken für den notwendigen Informationsaustausch, Flugdynamik, Regelungstechnik, insbesondere für verteilte / kooperative Steuerungstechniken, Graphentheorie für Kommunikationstopologie Modellierung und Sensoren-Technologie wie Differential GPS (DGPS). Für eine Flotte von Agenten, die in unmittelbarer Nähe fliegen, ist eine genaue Positionsbestimmung zwingend nötig um Kollisionen zu vermeiden und die Anforderungen für die meisten Missionen wie Georeferenzierung zu erfüllen. Für solche Szenarien ist DGPS ein potenzieller Kandidat. Ein Teil der Forschung konzentriert sich daher auf die Entwicklung von DGPS Code. Eines der Module dieser Forschung war Hardware-Implementierung. Ein einfacher Test-Aufbau zur Realisierung von Basisfunktionalitäten für Formationsflug von Quadrocoptern wurde am Lehrstuhl für Informationstechnik in der Luft- und Raumfahrt der Universität Würzburg entwickelt. Diese Testumgebung kann nicht nur zur Prüfung und Validierung von Algorithmen für Formationsflug in realer Umgebung genutzt werden, sondern dient auch zur Ausbildung von Studenten. Ein bereits vorhandener Prüfstand für einzelne Quadrocopter wurde mit den notwendigen Kommunikation und verteilten Steuerung erweitert, um Algorithmen für Formationsflüge in drei Freiheitsgraden (Roll / Nick / Gier) zu testen. Diese Studie umfasst die Bereiche der Kommunikation, Steuerungstechnik und Embedded-System-Programmierung. Das Bluetooth-Protokoll wurde für die gegenseitige Kommunikation zwischen zwei Quadrocoptern verwendet. Eine einfache Technik der Proportional-Integral-Differential (PID) Steuerung in Kombination mit Kalman-Filter wurde genutzt. Die MATLAB Instrument Control Toolbox wurde für die Datenanzeige, die Analyse und das Plotten verwendet. Plots können in Echtzeit gezeichnet werden und empfangene Daten können auch in Form von Dateien zur späteren Verwendung und Analyse gespeichert werden. Das System wurde preisgünstig, unter Berücksichtigung eines einfachen Aufbaus, entwickelt. Der vorgeschlagene Aufbau ist sehr flexibel und kann einfach an veränderte Anforderungen angepasst werden. Als verteiltes Steuerungsschema wurde ein zentralisierter, heterogener Formationsflug Positionsregler formuliert, der einen „explicit model following Linear Quadratic Regulator Proportional Integral (LQR PI)“ Regler verwendet. Der Anführer Quadrocopter ist ein stabiles Referenzmodell mit der gewünschten Dynamik, deren Ausgang vollkommen von den beiden Wingmen Quadrocopter verfolgt wird. Der Anführer selbst wird durch Pole Placement Steuerverfahren mit den gewünschten Stabilitätseigenschaften gesteuert, während die beiden Anhänger durch robuste und adaptive LQR PI Steuerverfahren geregelt werden. Für diese Studie wird ein Vollzustandsvektor der Quadrocopter betrachtet während nur die resultierende Leistung verfolgt wird. Die ausgewählte 3D Formationsgeometrie und die statische Stabilität bleibt unter einer Vielzahl von möglichen Störungen erhalten. Bei Kommunikationsverlust zwischen Anführer und einem der Anhänger, leitet der andere Anhänger die Daten, die er vom Anführer erhalten hat, an den betroffenen Anhänger weiter. Die Stabilität des Regelsystems wurde unter Verwendung von Singulärwerten analysiert. Der vorgeschlagene Ansatz für eng gekoppelten Formationsflug von MUAVs wurde mit Hilfe von umfangreichen Simulationen unter MATLAB® / Simulink® validiert und ergab viel versprechende Ergebnisse. Auch die Tracking-Leistung wurde für zeitlich veränderliche Befehle gezeigt. Die vorgeschlagene Architektur ist skalierbar und kann problemlos erweitert werden. Dieser Ansatz ist für die Szenarien geeignet, die eng gekoppelte Formationsflug benötigen, wie kooperatives Greifen oder gemeinsame Lasttransporte. Ein innovatives Framework für die Teamarbeit von zwei Quadrocopter Flotten wurde entwickelt. Als Beispielmission wurde ein Szenario gewählt, bei dem ein Feuer auf einer größeren Fläche gelöscht werden muss. Jede Formation hat ihre angegebene Formationsgeometrie und eine zugewiesene Aufgabe. Die Lageregelung für die Quadrocopter in einer der Formationen wurde durch ein LQR PI-Regelschema, das auf „explicit model following“ basiert, umgesetzt. Die Quadrocopter in anderen Formation werden durch ein LQR PI Servomechanismus Regelsystem gesteuert. Die beiden Steuersysteme werden in Bezug auf ihre Leistung und ihren Steuerungsaufwand verglichen. Beide Formationen werden durch entsprechende Bodenstationen durch virtuelle Anführer kommandiert. Die Bodenstationen tauschen die befohlene Höheninformation aus, um gegenseitig eine sichere Trennung zwischen den Formationen zu gewährleisten. Die Quadrocopter können kommandierte Solltrajektorien folgen und über erwünschten Punkten für eine vorgegebene Zeit schweben. Bei Kommunikationsverlust zwischen Bodenstation und einem der Quadcopter leitet der benachbarte Quadrocopter die Befehlsdaten, die er von der Bodenstation erhalten hat, an die betroffene Einheit weiter. Das vorgeschlagene Framework wurde durch umfangreiche Simulationen mit Hilfe von MATLAB® / Simulink® validiert und liefert sehr brauchbare Ergebnisse. Cluster-Rekonfiguration von Agenten wird in unserer Arbeit ebenfalls gezeigt. Dies erlaubt es die Formationsgeometrie während des Fluges auf eine beliebige neue Form umzuschalten. Für die genannten Anwendungen sind Konsens Algorithmen nicht erwünscht, da wir von den Quadrocopter Flotten fordern, dass sie dem von uns gewählten Weg folgen, und nicht ihren Weg selbst wählen. Eine Reihe der praktischen Probleme von Kommunikationsnetzen kann in geeigneter Weise durch Graphen dargestellt werden. Dies erleichtert die Problemformulierung und den Analyseprozess. Kommunikationstopologien für Netzwerke mit einer großen Anzahl von Einheiten, wie zum Beispiel Schwärme von Luftfahrzeugen, können durch einen graphentheoretischen Ansatz untersucht werden. Um die Bildung solcher Probleme zu erleichtern, wird der Graph mit Hilfe der Laplace-Matrix dargestellt. Eigenwerte der Laplace-Matrix wurden in unserer Studie angemessene Berücksichtigung gegeben einen Einblick in die Graphen / Subgraphen Eigenschaften zu verleihen. Der gleiche wurden genutzt um die bekannte Euler Formel zu verallgemeinern und somit auf Graphen und Subgraphen anwendbar zu machen. Eine modifizierte Euler-Formel wird ebenfalls vorgestellt. Die Verwendung der Graphentheorie in verteilten / kooperativen Regelsystemen wird auch durch Simulationen gezeigt. Kooperative Kontrolschemas, die auf auf Konsens-Algorithmen beruhenden, wurden für die Lageregelung von Quadrocopter-Flotten, in denen kein expliziter Anführer existiert, verwendet. Konsens-Algorithmen wurden in Kombination mit verschiedenen Steuersystemen verwendet, was zur Autonomie von Quadrocoptern beiträgt. Die Steuersysteme, die für diesen Zweck verwendet werden, umfassen LQR PI-Regelung basierend auf „model following“ und LQR PI Servo-Mechanismus. Die Regelungen wurden unter verschiedenen Kommunikationstopologien untersucht, darunter voll verbundene ungerichtete Graphen, gerichteten Graphen und Zyklus-Topologie. Der Informationsfluss unter den Agenten in einem Cluster wurde durch Laplace-Matrix modelliert. Die Auswirkungen von Eingangs Verzerrungen auf Konsens Werte wurden ebenfalls untersucht. Quadrocopter können durch gegenseitigen Konsens Flugbahnen verfolgen und die Zielpunkte erreichen. Die vorgeschlagenen Regelungssysteme wurden unter verschiedenen Kommunikationstopologien in Matlab / Simulink-Umgebung durch umfangreiche Simulationen validiert. Die Ergebnisse bescheinigen die Wirksamkeit der präsentierten Schemata mit dem zusätzlichen Vorteil der Einfachheit der Umsetzung. Das vorgeschlagene Regelungssystem ist skalierbar für große Gruppen von MUAVs. Für Formationsflug sind die Anforderungen an die Positionsgenauigkeit sehr hoch. GPS-Signale allein bieten keine ausreichend hohe Positionsgenauigkeit um die Anforderung zu erfüllen; eine Technik für die genauere Positionsbestimmung ist daher erforderlich, beispielsweise DGPS. Es existiert eine Anzahl von öffentlichen Codes für die GPS-Positionsbestimmung und Baseline-Bestimmung im Offline-Modus. Es existiert jedoch keine Software für DGPS, die Korrekturfaktoren der Basisstationen nutzt, ohne auf Doppel Differenz Informationen zu vertrauen. Um dies zu erreichen, wurde eine Methodik in MATLAB-Umgebung für DGPS mit C/A Pseudoranges nur auf einzelne Frequenz L1 eingeführt es machbar für Empfänger kostengünstig GPS zu nutzen. Unsere Basisstation wird an einem genau vermessen Referenzpunkt aufgestellt. Pseudoranges und geometrische Abstände werden an der Basisstation verglichen, um die Korrekturfaktoren zu berechnen. Diese Korrekturfaktoren, für aller gültigen Satelliten während einer Epoche, werden dann an einen Rover übergeben. Das Rover berücksichtigt innerhalb der entsprechenden Epoche diese für seine eigene wahre Positionsbestimmung. Zur Validierung der vorgeschlagenen Algorithmen wird unsere Rover ebenfalls an einer vorbestimmten Stelle platziert. Der vorgeschlagene Code ist ein geeignetes und einfaches Werkzeug für die Nachbearbeitung von GPS-Rohdaten für eine genaue Positionsbestimmung eines Rover, z.B. eines UAV während der Post-Missionsanalyse
Mini Unmanned Aerial Vehicles (MUAVs) are becoming popular research platform and drawing considerable attention, particularly during the last decade due to their afford- ability and multi-dimensional applications in almost every walk of life. MUAVs have obvious advantages over manned platforms including their much lower manufacturing and operational costs, risk avoidance for human pilots, flying safely low and slow, and realization of operations that are beyond inherent human limitations. The advancement in Micro Electro-Mechanical System (MEMS) technology, Avionics and miniaturization of sensors also played a significant role in the evolution of MUAVs. These vehicles range from simple toys found at electronic supermarkets for entertainment purpose to highly sophisticated commercial platforms performing novel assignments like offshore wind power station inspection and 3D modelling of buildings etc. MUAVs are also more environment friendly as they cause less air pollution and noise. Unmanned is therefore unmatched. Recent research focuses on use of multiple inexpensive vehicles flying together, while maintaining required relative separations, to carry out the tasks efficiently compared to a single exorbitant vehicle. Redundancy also does away the risk of loss of a single whole-mission dependent vehicle. Some of the valuable applications in the domain of cooperative control include joint load transportation, search and rescue, mobile communication relays, pesticide spraying and weather monitoring etc. Though realization of multi-UAV coupled flight is complex, however obvious advantages justify the laborious work involved