Relevant bibliographies by topics / Cooperative control

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Cooperative control'

Author: Grafiati
Published: 4 June 2021
Last updated: 8 June 2024

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Journal articles on the topic "Cooperative control"

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de Groot, Oscar, Laurens Valk, and Tamas Keviczky. "Cooperative Passivity-Based Control of Nonlinear Mechanical Systems." Robotics 12, no. 5 (October 9, 2023): 142. http://dx.doi.org/10.3390/robotics12050142.

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In this work, we propose two cooperative passivity-based control methods for networks of mechanical systems. By cooperatively synchronizing the end-effector coordinates of the individual agents, we achieve cooperation between systems of different types. The underlying passivity property of our control approaches ensures that cooperation is stable and robust. Neither of the two approaches rely on the modeling information of neighbors, locally, which simplifies the interconnection of applicable systems and makes the approaches modular in their use. Our first approach is a generalized cooperative Interconnection-and-Damping Assignment passivity-based control (IDA-PBC) scheme for networks of fully actuated and underactuated systems. Our approach leverages the definition of end-effector coordinates in existing single-agent IDA-PBC solutions for underactuated systems to satisfy the matching conditions, independently of the cooperative control input. Accordingly, our approach integrates a large set of existing single-agent solutions and facilitates cooperative control between these and fully actuated systems. Our second approach proposes agent outputs composed of their end-effector coordinates and velocities to guarantee cooperative stability for networks of fully actuated systems in the presence of communication delays. We validate both approaches in simulation and experiments.
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Majidah, Shinta, Yana Pratiwi, and Siwidyah Lastiani. "Peranan Teknologi Informasi Dalam Efektivitas Sistem Pengendalian Intern Koperasi Bina Citra Wanita." JFAS : Journal of Finance and Accounting Studies 5, no. 3 (October 20, 2023): 152–57. http://dx.doi.org/10.33752/jfas.v5i3.4760.

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This study aims to analyze the effect of the use of information technology on the effectiveness of the internal control system in the Bina Citra Women's Cooperative in Menganti Gresik. The research method used is qualitative, involving cooperative heads, cooperative treasurers, and cooperative members as informants. Data collection techniques were carried out through interviews with cooperative members and management, direct observation of activities in cooperatives, and study of documents such as cooperative SOPs, financial reports, and information technology usage policies. The results of the study show that cooperative members have a positive perception of the influence of the use of information technology in increasing the effectiveness of the cooperative's internal control system. Information technology helps in prioritizing customer service, preventing fraud, and reducing the risk of fraud
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Novikova, Yu O. "THE LEGAL REGULATION OF AGRICULTURAL COOPERATION DURING THE PERIOD OF THE PROVISIONAL GOVERNMENT AND SOVIET RUSSIA." Vestnik of Immanuel Kant Baltic Federal University Series Humanities and social science, no. 4 (2023): 5–21. http://dx.doi.org/10.5922/sikbfu-2023-4-1.

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The study examines the transformation of the legal status of agricultural cooperatives in Russia from the period when the Provisional Government came to power to 1929, the period when this type of cooperation was liquidated as a separate entity. The study demonstrates changes in cooperative legislation after the February Revolution of 1917 until the late 1920s — from expanding the democratic foundations of cooperative societies to the complete abolition of agricultural cooperation as a separate type of this socio-economic movement. The legislation of the Provisional Government on cooperation, including agricultural, expanded the rights of agricultural societies, established a unified legal status for all types of cooperatives, introduced the concept of a “cooperative society” into legal circulation for the first time, allowed cooperatives to form unions, and outlined a clear algorithm for the organization of cooperative activities. The period of “war communism” was characterized by extremely harsh measures regarding the state control of cooperatives. During the New Economic Policy, the legislator adopted imperial cooperative legislation, granting democratic rights and freedoms to cooperatives. This was driven by the difficult financial situation of the population, especially peasants, and the acute shortage of food products. The policy of building a socialist state determined the further fate of agricultural cooperation, as well as cooperation in general, transforming it from a private-law institution into a public-law one and thereby depriving it of the fundamental principles on which it had been built for several decades.
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Lytridis, Chris, Christos Bazinas, Ioannis Kalathas, George Siavalas, Christos Tsakmakis, Theodoros Spirantis, Eftichia Badeka, Theodore Pachidis, and Vassilis G. Kaburlasos. "Cooperative Grape Harvesting Using Heterogeneous Autonomous Robots." Robotics 12, no. 6 (October 28, 2023): 147. http://dx.doi.org/10.3390/robotics12060147.

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The development of agricultural robots is an increasingly popular research field aiming at addressing the widespread labor shortages in the farming industry and the ever-increasing food production demands. In many cases, multiple cooperating robots can be deployed in order to reduce task duration, perform an operation not possible with a single robot, or perform an operation more effectively. Building on previous results, this application paper deals with a cooperation strategy that allows two heterogeneous robots to cooperatively carry out grape harvesting, and its implementation is demonstrated. More specifically, the cooperative grape harvesting task involves two heterogeneous robots, where one robot (i.e., the expert) is assigned the grape harvesting task, whereas the second robot (i.e., the helper) is tasked with supporting the harvesting task by carrying the harvested grapes. The proposed cooperative harvesting methodology ensures safe and effective interactions between the robots. Field experiments have been conducted in order firstly to validate the effectiveness of the coordinated navigation algorithm and secondly to demonstrate the proposed cooperative harvesting method. The paper reports on the conclusions drawn from the field experiments, and recommendations for future enhancements are made. The potential of sophisticated as well as explainable decision-making based on logic for enhancing the cooperation of autonomous robots in agricultural applications is discussed in the context of mathematical lattice theory.
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Wuryani, Eni, and Merlyana Dwinda Yanthi. "Determining Factors of Corporate Governance in Women Corporative of East Java Indonesia." AKRUAL: Jurnal Akuntansi 11, no. 2 (October 1, 2020): 136. http://dx.doi.org/10.26740/jaj.v11n2.p136-148.

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All over the world want organizations to be sustainable, like organizations in Indonesia. Corporate governance (CG) implementation is a must in an organization. The application of corporate governance in Indonesia is applied to organizations in the form of cooperatives. The study aimed to determine factors of corporate governance in women corporative of East Java, Indonesia. Factors that include corporate governance are internal control, the rules for members, annual member meetings. The object of this study was 159 Cooperatives in East Java, Indonesia. The implementation of coporate governance in women's cooperatives has been going well, judging by the cooperative's performance appraisal. The implementation of internal control still needs to be improved. Cooperative members have mostly fulfilled their obligations as members through payment of basic contributions and mandatory contributions. The meeting held by members of most women's cooperatives was carried out on time. Cooperatives are microfinance institutions for cooperative members. Cooperatives are organizations that are established for the welfare of members. Implementation of corporate governance in women's cooperatives will improve cooperative performance.
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Priliandani, Ni Made Intan, Ni Made Rai Juniariani, and Ni Putu Sri Mariyatni. "PENGARUH UKURAN KOPERASI, JENIS KOPERASI SERTA PENGALAMAN KEPENGURUSAN MANAJEMEN TERHADAP KUALITAS SISTEM PENGENDALIAN INTERN PADA KOPERASI DI KABUPATEN TABANAN." Jurnal Aplikasi Akuntansi 3, no. 1 (December 18, 2018): 141–78. http://dx.doi.org/10.29303/jaa.v3i1.37.

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Cooperatives are a different organization with other businesses, such as BUMN and BUMD or government organizations. The uniqueness of cooperatives is that cooperatives are business units that have multiple identities in which each cooperative member is the owner and user of cooperative services. In order to be able to compete with other financial institutions, the cooperative must be able to determine a policy and strategy that must be developed and improved. One policy that can be taken to assist the development of cooperatives is the effectiveness of management control systems. Internal control is an activity that is influenced by the organization, coordinated methods and provisions to maintain organizational wealth, check accuracy, and reliability of accounting data, to improve business efficiency and encourage compliance with company regulations. The cooperative internal control system is influenced by several factors, namely the size of the cooperative, the type of cooperative, and the management experience of management. This study has the purpose of 1) whether the size of the cooperative influences the quality of the internal control system in cooperatives in Tabanan Regency. 2) whether the type of cooperative influences the quality of the internal control system in cooperatives in Tabanan Regency. 3) whether the management experience affects the quality of the internal control system in cooperatives in Tabanan Regency. This study uses primary data in the form of answers to questionnaires from supervisors and directors of cooperatives in Tabanan district. The sampling technique in this study is purposive sampling technique so that the sample in this study amounted to 35 cooperatives. The analysis technique used to answer the hypothesis is multiple linear regression. The results of the study show that 1) the size of the cooperative has a positive effect on the quality of the internal control system. 2) types of cooperatives have a positive effect on the quality of the internal control system. 3) management management experience has a positive effect on the quality of the internal control system.
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Giovanini, Leonardo. "Cooperative-feedback control." ISA Transactions 46, no. 3 (June 2007): 289–302. http://dx.doi.org/10.1016/j.isatra.2006.12.001.

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Golovina, Svetlana G., and Lidia N. Smirnova. "The opportunities of new cooperative models application in Russian agricultural economy." Tyumen State University Herald. Social, Economic, and Law Research 6, no. 1 (2020): 322–44. http://dx.doi.org/10.21684/2411-7897-2020-6-1-322-344.

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Agricultural cooperation in Russia is considered today as the most important condition for the successful functioning of the agricultural sector of the economy, as well as the development of rural areas and communities. However, as the results of theoretical and empirical analysis of domestic cooperative practices development demonstrate, cooperative activities, despite significant efforts by the State to support cooperation, are still low in efficiency. At the same time, one of the reasons for the current situation in the activities of agricultural consumer cooperatives is that their organizational model (traditional cooperatives) is unable to realize its potential in a new (rapidly changing) economic environment (both global and national). In this connection, the article 1) reveals the peculiarities of the conditions in which domestic cooperatives operate, as well as the problems they face in implementing strictly traditional principles in their organizational structure; 2) justifies the need to transform both the model of cooperatives and the formal and informal institutions that determine the development of cooperation in rural space; 3) highlights the main directions of traditional cooperative principles modification to bring cooperative structures to the new level of efficiency and competitiveness. The main result of the research is the conceptual definition of three alternative models of business-type cooperatives with different strategies, as well as different degrees of individualization property rights, control, and management. The common features of the proposed varieties of contemporary entrepreneurial cooperatives include the restriction of membership, the application of up-to-date financial instruments to enhance additional investment opportunities, the involvement of a wide range of participants in cooperative activities (as members, specialists, managers), and the implementation of various motivational tools for rapid expansion of cooperative activities. In conclusion, the author presents the algorithm of organizational and institutional changes, which are necessary for the successful introduction of the entrepreneurial model of agricultural cooperatives into domestic economic practice.
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Zhang, Fumin, and Naomi Ehrich Leonard. "Cooperative Filters and Control for Cooperative Exploration." IEEE Transactions on Automatic Control 55, no. 3 (March 2010): 650–63. http://dx.doi.org/10.1109/tac.2009.2039240.

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Ahmed, Sheeraz, Nadeem Javaid, Ashfaq Ahmad, Imran Ahmed, Mehr Yahya Durrani, Armughan Ali, Syed Bilal Haider, and Manzoor Ilahi. "SPARCO: Stochastic Performance Analysis with Reliability and Cooperation for Underwater Wireless Sensor Networks." Journal of Sensors 2016 (2016): 1–17. http://dx.doi.org/10.1155/2016/7604163.

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Reliability is a key factor for application-oriented Underwater Sensor Networks (UWSNs) which are utilized for gaining certain objectives and a demand always exists for efficient data routing mechanisms. Cooperative routing is a promising technique which utilizes the broadcast feature of wireless medium and forwards data with cooperation using sensor nodes as relays. Here, we present a cooperation-based routing protocol for underwater networks to enhance their performance called Stochastic Performance Analysis with Reliability and Cooperation (SPARCO). Cooperative communication is explored in order to design an energy-efficient routing scheme for UWSNs. Each node of the network is assumed to be consisting of a single omnidirectional antenna and multiple nodes cooperatively forward their transmissions taking advantage of spatial diversity to reduce energy consumption. Both multihop and single-hop schemes are exploited which contribute to lowering of path-losses present in the channels connecting nodes and forwarding of data. Simulations demonstrate that SPARCO protocol functions better regarding end-to-end delay, network lifetime, and energy consumption comparative to noncooperative routing protocol—improved Adaptive Mobility of Courier nodes in Threshold-optimized Depth-based routing (iAMCTD). The performance is also compared with three cooperation-based routing protocols for UWSN: Cognitive Cooperation (Cog-Coop), Cooperative Depth-Based Routing (CoDBR), and Cooperative Partner Node Selection Criteria for Cooperative Routing (Coop Re and dth).
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Dissertations / Theses on the topic "Cooperative control"

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Guo, Meng. "Quantized Cooperative Control." Thesis, KTH, Reglerteknik, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-55852.

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In this thesis project, we consider the cooperative control of multi-agent systems under limited communication between the individual agents. In particular, quantized values of the relatives states between neighboring agents are used as the control parameters for each agent. As an introductory part, the theoretical framework for the distributed consensus problem under perfect communication is reviewed with the focus on the system stability and convergence. We start from the common problem setup that single integrator agents with a static tree communication topology, where the stability constraints and convergence guaranty are derived for dierent quantization models: uniform, logarithmic and dynamic. Then the conclusions are extended to switching tree topologies, tree topologies with disconnected time intervals and nally general undirected graphs. The control performance like  onvergence rate and the area of convergence set are compared between systems with and without quantization eects, and also among the systems with dierent quantizers. Furthermore, similar techniques are applied to other system dynamics with quantized control inputs. We investigate additional constraints on the stability of the corresponding discrete time system due to the presence of quantization eects. Explicit upper bounds on the sampling time that guarantee convergence are derived. As expected, the sampling frequency has to be increased accordingly under dierent quantization models. The multi-agent system composed of second-order agents under general undirected communication graphs is also taken into account with quite dierent analytical tools. Finally we switch to an alternative model that takes the relative quantized states as control parameters instead. Distinctive convergence properties are found between these two models and detailed comparisons are made. Throughout this report, all results obtained are supported by numerical simulations.
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Sposato, Mario. "Multiagent cooperative coverage control." Thesis, KTH, Skolan för elektro- och systemteknik (EES), 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-187712.

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In this work, the problem of deploying a team of mobile sensing agents to provide coverage of an environment is addressed. We propose a novel distributed algorithm to generate a sequence of waypoints for each agent, based on intermittent communication between the agents. The algorithm is shown to converge to an equilibrium configuration, while a measure of the environment coverage is shown to be monotonically nondecreasing. To fulfill the task of moving the agents to the designated waypoints, we develop a non-linear control algorithm based on backstepping, as well as a path planning strategy that uses potential field navigation and collision avoidance. All the proposed algorithms are tested in a simulated environment and on real-world aerial robots.
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Woo, Sang-Bum. "Formation control for cooperative surveillance." [College Station, Tex. : Texas A&M University, 2008. http://hdl.handle.net/1969.1/ETD-TAMU-3203.

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Zhang, Fumin. "Geometric cooperative control of formations." College Park, Md. : University of Maryland, 2004. http://hdl.handle.net/1903/1994.

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Thesis (Ph. D.) -- University of Maryland, College Park, 2004.
Thesis research directed by: Electrical Engineering. Title from t.p. of PDF. Includes bibliographical references. Published by UMI Dissertation Services, Ann Arbor, Mich. Also available in paper.
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Alabri, Said. "Distributed Extremum Seeking and Cooperative Control for Mobile Cooperative Communication Systems." Master's thesis, University of Central Florida, 2013. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/5596.

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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
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Savage, Elizabeth. "Cooperative control of autonomous underwater vehicles." [College Station, Tex. : Texas A&M University, 2003. http://hdl.handle.net/1969.1/236.

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Thesis (MS)--Texas A&M University, 2003.
"Major Subject: Aerospace Engineering" Title from author supplied metadata (automated record created on Jul. 18, 2005.) Vita. Abstract. Includes bibliographical references.
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Yale, Gary E. "Cooperative control of multiple space manipulators." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 1993. http://handle.dtic.mil/100.2/ADA270291.

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Dissertation (Ph.D. in Aeronautical and Astronautical Engineering) Naval Postgraduate School, September 1993.
Dissertation supervisor(s): Agrawal, Brij N. "September 1993." Includes bibliographical references. Also available online.
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Ilaya, Omar, and o. ilaya@student rmit edu au. "Cooperative Control for Multi-Vehicle Swarms." RMIT University. Aerospace, Mechanical & Manufacturing Engineering, 2009. http://adt.lib.rmit.edu.au/adt/public/adt-VIT20091027.112852.

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The cooperative control of large-scale multi-agent systems has gained a significant interest in recent years from the robotics and control communities for multi-vehicle control. One motivator for the growing interest is the application of spatially and temporally distributed multiple unmanned aerial vehicle (UAV) systems for distributed sensing and collaborative operations. In this research, the multi-vehicle control problem is addressed using a decentralised control system. The work aims to provide a decentralised control framework that synthesises the self-organised and coordinated behaviour of natural swarming systems into cooperative UAV systems. The control system design framework is generalised for application into various other multi-agent systems including cellular robotics, ad-hoc communication networks, and modular smart-structures. The approach involves identifying suitable relationships that describe the behaviour of the UAVs within the swarm and the interactions of these behaviours to produce purposeful high-level actions for system operators. A major focus concerning the research involves the development of suitable analytical tools that decomposes the general swarm behaviours to the local vehicle level. The control problem is approached using two-levels of abstraction; the supervisory level, and the local vehicle level. Geometric control techniques based on differential geometry are used at the supervisory level to reduce the control problem to a small set of permutation and size invariant abstract descriptors. The abstract descriptors provide an open-loop optimal state and control trajectory for the collective swarm and are used to describe the intentions of the vehicles. Decentralised optimal control is implemented at the local vehicle level to synthesise self-organised and cooperative behaviour. A deliberative control scheme is implemented at the local vehicle level that demonstrates autonomous, cooperative and optimal behaviour whilst the preserv ing precision and reliability at the local vehicle level.
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Dutta, Rajdeep. "Cooperative control of autonomous network topologies." Thesis, The University of Texas at San Antonio, 2016. http://pqdtopen.proquest.com/#viewpdf?dispub=10151348.

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In this dissertation, we present novel solutions to cooperative control of autonomous multi-agent network topologies pertaining to the area of hostile target tracking by multiple unmanned aerial vehicles (UAVs). The present work assumes an undirected graph comprising point-mass UAVs with time-varying communication topology among agents. The level of information sharing ability among agents in a multi-agent network, i.e. the network connectivity, plays pivotal role in group dynamics. A neighborhood information based decentralized controller is proposed in order to drive UAVs into a symmetric formation of polygon shape surrounding a mobile target, simultaneously with maintaining and controlling connectivity during the formation process. Appropriate controller parameter selection schemes, both for controller weights and gains, are adapted for dynamic topologies to maintain the connectivity measure above zero at all times. A challenging task of tracking a desired connectivity profile along with the formation control, is accomplished by using time-varying controller gains throughout agents dynamics. We next present a generalized formation controller, which in fact generates a family of UAV trajectories satisfying the control criteria. The proposed decentralized controller contains additional tuning parameters as fractional powers on proportional and derivative terms, rendering flexibility in achieving the control objective. The proposed controller with proper fractional powers, results in gradual state changes in UAV dynamics by using limited control inputs. Moreover, we extend our work by addressing a ground target tracking and reacquiring problem using the visual information gathered by flying UAV. The proposed guidance law uses line-of-sight guidance to track the target pushing it towards the image center captured by UAV, and exploits UAV-target mutual information to reacquire the target in case it steers away from the field-of-view for a short time. The convergence of the closed loop systems under the proposed controllers are shown using Lyapunov theory. Simulation results validate the effectiveness and novelty of the proposed control laws.

In addition to the above, this work focuses on categorizing multi-agent topologies in concern with the network dynamics and connectivity to analyze, realize, and visualize multi-agent interactions. In order to explore various useful agents reconfiguration possibilities without compromising the network connectivity, the present work aims at determining distinct topologies with the same connectivity or isoconnected topologies. Different topologies with identical connectivity are found out with the help of analytic techniques utilizing matrix algebra and calculus of variation. Elegant strategies for preserving connectivity in a network with a single mobile agent and rest of the stationary members, are proposed in this work as well. The proposed solutions are validated with the help of sufficient examples. For visual understanding of how agents locations and topology configurations influence the network connectivity, a MATLAB based graphical user interface is designed to interact with multi-agent graphs in a user-friendly manner.

To this end, the present work succeeds to determine solutions to challenging multi-UAV cooperative control problems, such as: (1) Symmetric formation control surrounding a mobile target; (2) Maintaining, improving and controlling the network connectivity during a mission; and (3) Categorizing different multi-agent topologies to unravel useful reconfiguration options for a group. The proposed theories with appropriate analysis, and the simulation results suffice to show the contribution and novelty of this work.

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Nelson, Derek R. "Cooperative Control of Miniature Air Vehicles." BYU ScholarsArchive, 2005. https://scholarsarchive.byu.edu/etd/1095.

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Cooperative control for miniature air vehicles (MAVs) is currently a highly researched topic. There are many application for which MAVs are well suited, including fire monitoring, surveillance and reconaissance, and search and rescue missions. All of these applications can be carried out more effictively by a team of MAVs than by a single vehicle. As technologies for microcontrollers and small sensors have improved so have the capabilities of MAVs. This improvement in MAV performance abilities increases the possibility for cooperative missions. The focus of this research was on cooperative timing missions. The issues faced when dealing with multi-MAV flight include information transfer, real time path planning, and maintenance of a fleet of flight-worthy MAVs. Additional challenges associated with timing missions include path following and velocity control. Two timing scenarios were studied and both of these scenarios were flight tested. The first scenario was a sequenced arrival of the MAVs over a target at a predetermined fly-through heading. The second scenario was a simultaneous arrival of the team ofMAVs over a known target location. The ideas of coordination functions and coordination variables have been employed to achieve coordination. Experimental results verify the feasibility of real time coperative control for a team of MAVs. Initial cooperative timing tests revealed the need for more accurate path following. Accordingly, a new method for path following using vector fields was developed. A vector field of desired ground track headings is calculated and commanded ground track headings are calculated such that ground track heading error and lateral following error decay asymptotically even in the presence of constant wind disturbances. The utilization of ground track heading and ground speed in the path following control, in combination with the vector field methods is what makes this zero-error following possible. Methods for following straight lines and orbits as well as combinations of the lines and circular arcs are presented. The assertions that minimal following errors result when using these methods have been verified experimentally.
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Books on the topic "Cooperative control"

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Kumar, Vijay, Naomi Leonard, and A. Stephen Morse, eds. Cooperative Control. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/b99788.

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Bai, He, Murat Arcak, and John Wen. Cooperative Control Design. New York, NY: Springer New York, 2011. http://dx.doi.org/10.1007/978-1-4614-0014-1.

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Guo, Yi. Distributed Cooperative Control. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2017. http://dx.doi.org/10.1002/9781119216131.

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Robert, Murphey, and Pardalos P. M. 1954-, eds. Cooperative control and optimization. Dordrecht: Kluwer Academic Publishers, 2002.

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Murphey, Robert, and Panos M. Pardalos, eds. Cooperative Control and Optimization. Boston, MA: Springer US, 2002. http://dx.doi.org/10.1007/b130435.

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K, Schmidt D., and Langley Research Center, eds. Extended cooperative control synthesis. Hampton, Va: National Aeronautics and Space Administration, Langley Research Center, 1994.

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Hirsch, Michael J., Clayton W. Commander, Panos M. Pardalos, and Robert Murphey, eds. Optimization and Cooperative Control Strategies. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-540-88063-9.

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Pettersen, Kristin Y., Jan Tommy Gravdahl, and Henk Nijmeijer, eds. Group Coordination and Cooperative Control. Berlin/Heidelberg: Springer-Verlag, 2006. http://dx.doi.org/10.1007/11505532.

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1954-, Pardalos P. M., ed. Cooperative networks: Control and optimization. Cheltenham, UK: Edward Elgar, 2008.

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1954-, Larsen Jeffrey Arthur, and Wirtz James J. 1958-, eds. Arms control and cooperative security. Boulder, Colo: Lynne Rienner Publishers, 2009.

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Book chapters on the topic "Cooperative control"

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Baillieul, J. "The Geometry of Sensor Information Utilization in Nonlinear Feedback Control of Vehicle Formations." In Cooperative Control, 1–24. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-31595-7_1.

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Ren, Wei, Randal W. Beard, and Timothy W. McLain. "Coordination Variables and Consensus Building in Multiple Vehicle Systems." In Cooperative Control, 171–88. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-31595-7_10.

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Sepulchre, Rodolphe, Derek Paley, and Naomi Leonard. "Collective Motion and Oscillator Synchronization." In Cooperative Control, 189–205. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-31595-7_11.

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Slotine, Jean-Jacques E., and Wei Wang. "A Study of Synchronization and Group Cooperation Using Partial Contraction Theory." In Cooperative Control, 207–28. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-31595-7_12.

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Tanner, Herbert G., Ali Jadbabaie, and George J. Pappas. "Flocking in Teams of Nonholonomic Agents." In Cooperative Control, 229–39. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-31595-7_13.

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Zhang, Fan, Ben Grocholsky, Vijay Kumar, and Max Mintz. "Cooperative Control for Localization of Mobile Sensor Networks." In Cooperative Control, 241–55. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-31595-7_14.

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Lin, J., A. S. Morse, and B. D. O. Anderson. "The Multi-Agent Rendezvous Problem. An Extended Summary." In Cooperative Control, 257–89. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-31595-7_15.

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Bertozzi, Andrea L., Mathieu Kemp, and Daniel Marthaler. "Determining Environmental Boundaries: Asynchronous Communication and Physical Scales." In Cooperative Control, 25–42. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-31595-7_2.

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Bullo, Francesco, and Jorge Cortés. "Adaptive and Distributed Coordination Algorithms for Mobile Sensing Networks." In Cooperative Control, 43–62. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-31595-7_3.

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Fierro, Rafael, and Kirk Wesselowski. "Optimization-Based Control of Multi-Vehicle Systems." In Cooperative Control, 63–78. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-31595-7_4.

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Conference papers on the topic "Cooperative control"

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Asadi, Fatemeh, and Arthur Richards. "Cooperative conflict resolution by velocity obstacle method." In 2014 UKACC International Conference on Control (CONTROL). IEEE, 2014. http://dx.doi.org/10.1109/control.2014.6915214.

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McIntyre, David, Wasif Naeem, and Xiandong Xu. "Cooperative obstacle avoidance using bidirectional artificial potential fields." In 2016 UKACC 11th International Conference on Control (CONTROL). IEEE, 2016. http://dx.doi.org/10.1109/control.2016.7737540.

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Shin, Hyo-Sang, Cedric Leboucher, and Antonios Tsourdos. "Resource allocation with cooperative path planning for multiple UAVs." In 2012 UKACC International Conference on Control (CONTROL). IEEE, 2012. http://dx.doi.org/10.1109/control.2012.6334646.

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Manoharan, Amith. "Strategies for Cooperative UAVs Using Model Predictive Control." In Twenty-Ninth International Joint Conference on Artificial Intelligence and Seventeenth Pacific Rim International Conference on Artificial Intelligence {IJCAI-PRICAI-20}. California: International Joint Conferences on Artificial Intelligence Organization, 2020. http://dx.doi.org/10.24963/ijcai.2020/738.

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Abstract:
Unmanned aerial vehicles (UAVs) have reached significant maturity over several years for safe civilian operations like mapping, search and rescue. The operation performance can be significantly improved by deploying multiple cooperating UAVs and optimal decision making. In this work, we present the use of nonlinear model predictive control (NMPC) for two different applications involving cooperative UAVs.
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Rosero, Esteban, and Herbert Werner. "Cooperative source seeking via gradient estimation and formation control (Part 1)." In 2014 UKACC International Conference on Control (CONTROL). IEEE, 2014. http://dx.doi.org/10.1109/control.2014.6915212.

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Rosero, Esteban, and Herbert Werner. "Cooperative source seeking via gradient estimation and formation control (Part 2)." In 2014 UKACC International Conference on Control (CONTROL). IEEE, 2014. http://dx.doi.org/10.1109/control.2014.6915213.

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Chandler, P. R., M. Pachter, and S. Rasmussen. "UAV cooperative control." In Proceedings of American Control Conference. IEEE, 2001. http://dx.doi.org/10.1109/acc.2001.945512.

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Zhang, Fumin, and Naomi Ehrich Leonard. "Cooperative Kalman filters for cooperative exploration." In 2008 American Control Conference (ACC '08). IEEE, 2008. http://dx.doi.org/10.1109/acc.2008.4586893.

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Hu, Junyan, and Alexander Lanzon. "Cooperative Control of Innovative Tri-Rotor Drones Using Robust Feedback Linearization." In 2018 UKACC 12th International Conference on Control (CONTROL). IEEE, 2018. http://dx.doi.org/10.1109/control.2018.8516820.

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Tomic, Ivana, Efstathios Milonidis, and George D. Halikias. "LQR distributed cooperative control of a formation of low-speed experimental UAVs." In 2016 UKACC 11th International Conference on Control (CONTROL). IEEE, 2016. http://dx.doi.org/10.1109/control.2016.7737541.

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Reports on the topic "Cooperative control"

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Barth, Eric J. Agent-Based Cooperative Control. Fort Belvoir, VA: Defense Technical Information Center, December 2005. http://dx.doi.org/10.21236/ada446345.

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Feddema, John Todd, Eric Paul Parker, John S. Wagner, and David Alan Schoenwald. Analysis and control of distributed cooperative systems. Office of Scientific and Technical Information (OSTI), September 2004. http://dx.doi.org/10.2172/919643.

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How, Jonathan P. Control Architecture Design and Demonstration for Cooperative UAV's. Fort Belvoir, VA: Defense Technical Information Center, April 2008. http://dx.doi.org/10.21236/ada484530.

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Hurtado, John E. Distributed Sensing & Cooperative Control for Plume Tracing. Fort Belvoir, VA: Defense Technical Information Center, January 2000. http://dx.doi.org/10.21236/ada410645.

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Campbell, Mark E. Modeling for Semi-Autonomous Control of Cooperative Vehicles. Fort Belvoir, VA: Defense Technical Information Center, January 2009. http://dx.doi.org/10.21236/ada505176.

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Krishnaprasad, P. S. Gyroscopic Many Body Problems in Cooperative and Adversarial Control. Fort Belvoir, VA: Defense Technical Information Center, April 2010. http://dx.doi.org/10.21236/ada533583.

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Parker, Lynne E. Local Versus Global Control Laws for Cooperative Agent Teams. Fort Belvoir, VA: Defense Technical Information Center, March 1992. http://dx.doi.org/10.21236/ada259338.

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Young, Joseph G. A cooperative control algorithm for camera based observational systems. Office of Scientific and Technical Information (OSTI), January 2012. http://dx.doi.org/10.2172/1034889.

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Rakha, Hesham, Kyoungho Ahn, Ihab Elshawarby, Jianhe Du, Hao Chen, Youssef Bichiou, Hossam Abdelghaffar, Karim Fadhloun Karim Fadhloun, Mohamed Farag, and Maha Elouni. Developing an Eco-Cooperative Automated Control System (Eco-CAC). Office of Scientific and Technical Information (OSTI), June 2021. http://dx.doi.org/10.2172/1798876.

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Wood, Scott D. Cooperative Interface Agents for Networked Command, Control, and Communications (CIANC3). Fort Belvoir, VA: Defense Technical Information Center, April 2003. http://dx.doi.org/10.21236/ada414232.

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