Letteratura scientifica selezionata sul tema "Delayed-Outputs"

Un système dynamique modélise l'évolution d'un système au fil du temps, régie par des lois ou des équations spécifiques. Assurer la stabilité de ces systèmes, sous une action de contrôle donnée, est essentiel pour prévoir leur comportement à long terme. Les méthodes d'analyse de stabilité, telles que la théorie de Lyapunov et la stabilité entrée-état (ISS), fournissent des outils essentiels pour évaluer si un système restera stable. Lorsque la mesure directe de tous les états du système n'est pas possible, des techniques d'estimation, telles que les observateurs et les estimateurs, jouent un rôle crucial en reconstruisant les états internes à partir des mesures disponibles, permettant ainsi un contrôle en retour de sortie efficace. Le développement de schémas d'estimation avancés et de méthodes de conception d'observateurs constitue la principale motivation de cette thèse. Dans ce cadre, trois contributions majeures sont proposées dans cette thèse, détaillées ci-dessous :1. Analyse des schémas d'estimation à horizon glissant robuste (MHE) : Comme la propriété de stabilité exponentielle incrémentale entrée/sortie-état (i-EIOSS) est nécessaire pour synthétiser les paramètres de la fonction de coût dans le contexte du MHE, deux procédures de conception numérique sont d'abord proposées pour garantir qu'un système non linéaire réalise la propriété i-EIOSS et pour calculer les paramètres i-EIOSS associés. Ensuite, la stabilité robuste de l'estimation en horizon glissant (MHE) est prouvée. De nouvelles conditions de conception sont établies et des techniques de prédiction avancées sont introduites. 2. Contributions aux observateurs basés sur les LMIs et les observateurs à grand-gain : Ce chapitre est divisé en deux parties : la première partie traite de la conception d'observateurs pour des systèmes non linéaires via des inégalités matricielles linéaires (LMIs). L'objectif principal est de montrer que, pour certaines familles de systèmes non linéaires, les techniques de conception d'observateurs basées sur les LMIs fournissent toujours des observateurs exponentiellement convergents. La deuxième partie concerne la méthodologie des observateurs à grand-gain. Une nouvelle méthode de conception est proposée pour des systèmes avec des structures non linéaires arbitraires, contrairement aux résultats standards sur la méthodologie des observateurs à grand-gain développés pour les non-linéarités triangulaires. 3. Contributions à la conception d'observateurs pour des systèmes non linéaires avec des mesures retardées : L'idée principale consiste à utiliser une technique d'extension dynamique pour transformer un système avec des sorties non linéaires retardées en un système avec des sorties linéaires et un terme intégral dépendant du retard dans le processus dynamique. Sur la base de cette transformation, de nouvelles conditions de synthèse moins contraignantes sont établies, garantissant la convergence exponentielle de l'observateur malgré les valeurs élevées du retard dans les mesures de sortie
A dynamical system models how a system evolves over time, governed by specific laws or equations. Ensuring the stability of such systems, under a given control action, is vital for predicting their long-term behavior. Stability analysis methods, such as Lyapunov's theory and Input-to-State Stability (ISS), provide essential tools to assess whether a system will remain stable. When direct measurements of all system states are not possible, estimation techniques, such as observers and estimators, play a crucial role in reconstructing internal states from available measurements, enabling effective feedback control. Then, developing advanced estimation schemes and observer design methods is the main motivation of this thesis. Towards this end, three major contributions are proposed in this thesis, as detailed below : 1. Analysis of Robust Moving Horizon Estimation (MHE) Schemes: Since the incremental exponential input/output-to-state stability (i-EIOSS) property is required to synthesize the parameters of the cost function in the MHE context, then, first, two numerical design procedures are proposed to ensure that a nonlinear system achieves i-EIOSS property and to compute the associated i-EIOSS parameters. Then, the robust stability of moving horizon estimation (MHE) is proven. Novel design conditions are established and advanced predictions techniques are introduced. 2. Contributions to LMI-based and high-gain-based Observers: This chapter is split into two parts: the first part deals with observer design for nonlinear systems via Linear Matrix Inequalities(LMIs). The main goal consists of showing that for some families of nonlinear systems, the LMI-based observer design techniques always provide an exponential convergent observer. The second part deals with high-gain observer methodology. A novel design method is proposed for systems with arbitrary nonlinear structures contrary to the standard results on high-gain observer methodology developed for triangular nonlinearities. 3. Contributions to observer design for nonlinear systems with delayed measurements: The main idea behind this consists of using a dynamic extension technique to transform a system with delayed nonlinear outputs into a system with linear outputs and a delay-dependent integral term in the dynamic process. Based on this transformation, novel and less conservative synthesis conditions are established, ensuring the exponential convergence of the observer despite the large values of the delay in the output measurements

Abstract Gas turbine combustors employing lean premixed combustion are prone to combustion instability. Combustion instability, if unchecked, will have deleterious effects to the combustor and hence needs to be controlled. Active control methods are preferred to obtain better off-design performance. The effectiveness of active control methods is dependent on the quality of controller which in-turn depends on the quality of model. In the present work, an input-output model structure, where the output of the system at the current instant is modelled as a nonlinear function of delayed inputs and outputs is chosen. As there are infinite possibilities for representation of nonlinear functions, all parameters in the model structure like time delay between input and output, number of delayed input and output terms and the appropriate form of nonlinear function can be obtained only iteratively. However, prior knowledge of delay and number of delayed inputs and outputs reduces the computational intensity. To this end, the present work utilizes the method of Lipschitz indices to obtain the number of delayed inputs and outputs.

In bilateral teleoperation, the operator holds a local robot which determines the motion of a remote robot and continuously receives delayed force feedback. Transparency is a measure of teleoperation system fidelity. The ideal teleoperator system is the identity channel, in which there is neither delay nor distortion. During the last decades transparency was widely analyzed using two-port hybrid representation of the system in Laplace domain. Such representations define hybrid matrix that maps between the transmission channel inputs and outputs. However, in measuring transparency one should consider also the human operator, and therefore we propose a multidimensional measure of transparency which takes into account: i) Perceptual transparency: The human operator cannot distinguish when the teleoperation channel is being replaced by an identity channel. ii) Local Motor transparency: The movement of the operator does not change when the teleoperation channel is replaced by an identity channel. iii) Remote transparency: The movement of the remote robot does not change when the teleoperation channel is replaced by an identity channel. We hypothesize that by selecting filters and training protocol it is possible to obtain perceptually transparent teleoperation (i) and remote motor transparency (iii) without local motor transparency (ii), namely, to transparentize the system. We formally define the transparency error, analyze this process in the linear case, and simulate simplified teleoperation system according to typical experimental results in our previous studies about perception of delayed stiffness. We believe that these tools are essential in developing functional teleoperation systems.

The PRCI Project #417-203902 - ROW 3-1-A Final Report is attached for Member review and comment. The report includes a summary of all work completed in all Tasks which include: - Catalog, taxonomy, and sample data set for the threats detected. - Benchmarks of the sensitivity, accuracy, reliability, and robustness of an automated multi sensor, multi-threat detection and near real-time reporting comparing performance on conventional aircraft and UAS. - Technical synopsis for operators on integrating automated near real-time aerial threat reports into pipeline performance and safety improvement programs. - Report on status of integrating UAS into the National Airspace System in an application that contributes to improving the safety and integrity of the Nation's critical pipeline infrastructure. The project is complete. Full testing on the multi-spectral sensor is complete and Flight 4 of Phase 1 Flight Tests, scheduled for Oct/Nov 2021 was completed with approval of a no-cost extension in 2022. These delayed tasks are excusable due to delays caused in 2020 and 2021 by Novel Coronavirus (2019-nCoV), inclement weather and wildfires impacting several western states, and aviation delays (i.e., licenses from government authorities, misrepresentation of the specification and performance of the Sentera camera), which caused impacts to the contractor's capability to maintain a schedule under ROW 3-1-A and were completed under extension under ROW-3-1. The scope for this research project is to integrate PRCI Project ROW-3-1 multi-threat sensors, algorithms and communications systems onto the unmanned aircraft system (UAS); select Test Range(s) and complete Threat Staging Planning, while developing an Aviation Safety Case to the FAA for use of long endurance UAS on pipeline patrol. In addition, the project includes conducting UAS Test Program flights with automated multi-threat detection system on long endurance UAS flying hundreds of miles of pipeline corridor and perform analysis of data, benchmark automated threat detection system and UAS performance, report on advances in the integration of the remote sensing platform outputs with existing pipeline operator performance and safety programs. Lastly, it provided data of value to the FAA with respect to the integration of long-range Unmanned Aircraft Systems (UASs) into the National Airspace System. The program objectives stated in the contract include: - Produce a data set that enables benchmarking the sensitivity, accuracy, reliability and robustness of an automated multi-sensor, multi-threat detection and near real-time reporting system operating on a long-range Unmanned Aircraft System (UAS) for damage prevention and other pipeline integrity applications. - Generate data to compare and benchmark the detection and reporting system operating on conventional aircraft and UAS and with standard patrol methods for evaluating the value of integrating generated threat reports into performance and safety improvement programs. - Provide data to the United States Department of Transportation (US DOT) Federal Aviation Administration (FAA), PHMSA, and the PRCI research team to assist with information for safe integration of UAS into the National Airspace System for pipeline infrastructure.