Distributed Cooperative Control and Optimization for Multi-Agent Systems

Wang, Qing Xin, Bin Chen Jie
Innbundet / 2025 / Engelsk

Produktdetaljer

ISBN
9789819609499
Publisert
2025-03-22
Utgiver
Vendor
Springer Nature Switzerland AG
Høyde
235 mm
Bredde
155 mm
Aldersnivå
Research, P, 06
Språk
Product language
Engelsk
Format
Product format
Innbundet

Forfatter
Wang, Qing
Xin, Bin
Chen Jie

Om bidragsyterne

Qing Wang received the B.Eng. and Ph.D. degrees in control science and engineering from the School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing, China, in 2013 and 2018, respectively. She is currently a lecturer at the School of Automation, Beijing Institute of Technology. Her current research interests include multi-agent systems, nonlinear systems, intelligent control, and distributed optimization.

 

Bin Xin received the B.S. degree in information engineering and the Ph.D. degree in control science and engineering from the Beijing Institute of Technology, Beijing, China, in 2004 and 2012, respectively. He was an academic visitor at the Decision and Cognitive Sciences Research Centre at the University of Manchester from 2011 to 2012. He is currently a professor at the School of Automation, Beijing Institute of Technology. His current research interests include search and optimization, evolutionary computation, unmanned systems, and multi-agent systems.

 

Jie Chen received the B.S., M.S., and Ph.D. degrees in control theory and control engineering from the Beijing Institute of Technology, Beijing, China, in 1986, 1996, and 2001, respectively. He was the President of Tongji University, Shanghai, China, during 2018-2023. He is a Professor with the Control Science and Engineering, Beijing Institute of Technology and Tongji University, where he serves as the Director of the National Key Laboratory of Autonomous Intelligent Unmanned Systems (KAIUS). He is the academician of the Chinese Academy of Engineering and the fellow of the IEEE and IFAC. His current research interests include complex systems, multiagent systems, multiobjective optimization and decision, and constrained nonlinear control.

 

Distributed Cooperative Control and Optimization for Multi-Agent Systems

Wang, Qing Xin, Bin Chen Jie
Innbundet / 2025 / Engelsk
Wang, Qing Xin, Bin Chen Jie
Innbundet / 2025 / Engelsk
Nettpris:
2.201,-
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This book provides a concise and in-depth exposition of distributed control and optimization problems of multi-agent systems. The book integrates various ideas and tools from dynamic systems, control theory, graph theory, and optimization to address the special challenges posed by such complexities in the environment as communication delay, topological dynamics, and environmental uncertainties. In order to deal with the mismatched uncertainties and time delay, observer-based controller and sliding mode control are developed to achieve consensus control. When there is a leader or multiple leaders in the communication topologies, containment control is required. The book studies both state and output containment for nonlinear multi-agent systems with undirected or directed networks. Furthermore, event-triggered schemes are proposed to reduce communication and computation costs. Distributed optimization for multi-agent systems is an interesting topic that has attracted more and more attention due to its wide range of applications such as smart grids, sensor networks, and mobile manipulators. In distributed optimization, the goal is to optimize the global cost function, which is the sum of all local cost functions, each of which is known only by its own local agent. Distributed nonsmooth convex optimization for multi-agent systems based on proximal operators is developed to achieve distributed optimal consensus.
Les mer
This book provides a concise and in-depth exposition of distributed control and optimization problems of multi-agent systems.
Introduction.- Disturbance observer-based sliding mode control for multi-agent systems with mismatched uncertainties.- Observer-based containment for a class of nonlinear multi-agent systems with time-delayed protocols.- Robust output containment control of multi-agent systems with unknown heterogeneous nonlinear uncertainties in directed networks.- Distributed event-based consensus control of multi-agent system with matching nonlinear uncertainties.
Les mer
This book provides a concise and in-depth exposition of distributed control and optimization problems of multi-agent systems. The book integrates various ideas and tools from dynamic systems, control theory, graph theory, and optimization to address the special challenges posed by such complexities in the environment as communication delay, topological dynamics, and environmental uncertainties. In order to deal with the mismatched uncertainties and time delay, observer-based controller and sliding mode control are developed to achieve consensus control. When there is a leader or multiple leaders in the communication topologies, containment control is required. The book studies both state and output containment for nonlinear multi-agent systems with undirected or directed networks. Furthermore, event-triggered schemes are proposed to reduce communication and computation costs. Distributed optimization for multi-agent systems is an interesting topic that has attracted more and more attention due to its wide range of applications such as smart grids, sensor networks, and mobile manipulators. In distributed optimization, the goal is to optimize the global cost function, which is the sum of all local cost functions, each of which is known only by its own local agent. Distributed nonsmooth convex optimization for multi-agent systems based on proximal operators is developed to achieve distributed optimal consensus.
Les mer
Includes both linear and nonlinear multi-agent systems showing better performance with the proposed methods Introduces both distributed optimization and control methods for multi-agent systems Proposes practical and feasible methods for dynamics of multi-agent systems in general
Les mer
GPSR Compliance The European Union's (EU) General Product Safety Regulation (GPSR) is a set of rules that requires consumer products to be safe and our obligations to ensure this. If you have any concerns about our products you can contact us on ProductSafety@springernature.com. In case Publisher is established outside the EU, the EU authorized representative is: Springer Nature Customer Service Center GmbH Europaplatz 3 69115 Heidelberg, Germany ProductSafety@springernature.com
Les mer

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This book provides a concise and in-depth exposition of distributed control and optimization problems of multi-agent systems. The book integrates various ideas and tools from dynamic systems, control theory, graph theory, and optimization to address the special challenges posed by such complexities in the environment as communication delay, topological dynamics, and environmental uncertainties. In order to deal with the mismatched uncertainties and time delay, observer-based controller and sliding mode control are developed to achieve consensus control. When there is a leader or multiple leaders in the communication topologies, containment control is required. The book studies both state and output containment for nonlinear multi-agent systems with undirected or directed networks. Furthermore, event-triggered schemes are proposed to reduce communication and computation costs. Distributed optimization for multi-agent systems is an interesting topic that has attracted more and more attention due to its wide range of applications such as smart grids, sensor networks, and mobile manipulators. In distributed optimization, the goal is to optimize the global cost function, which is the sum of all local cost functions, each of which is known only by its own local agent. Distributed nonsmooth convex optimization for multi-agent systems based on proximal operators is developed to achieve distributed optimal consensus.
Les mer
This book provides a concise and in-depth exposition of distributed control and optimization problems of multi-agent systems.
Introduction.- Disturbance observer-based sliding mode control for multi-agent systems with mismatched uncertainties.- Observer-based containment for a class of nonlinear multi-agent systems with time-delayed protocols.- Robust output containment control of multi-agent systems with unknown heterogeneous nonlinear uncertainties in directed networks.- Distributed event-based consensus control of multi-agent system with matching nonlinear uncertainties.
Les mer
This book provides a concise and in-depth exposition of distributed control and optimization problems of multi-agent systems. The book integrates various ideas and tools from dynamic systems, control theory, graph theory, and optimization to address the special challenges posed by such complexities in the environment as communication delay, topological dynamics, and environmental uncertainties. In order to deal with the mismatched uncertainties and time delay, observer-based controller and sliding mode control are developed to achieve consensus control. When there is a leader or multiple leaders in the communication topologies, containment control is required. The book studies both state and output containment for nonlinear multi-agent systems with undirected or directed networks. Furthermore, event-triggered schemes are proposed to reduce communication and computation costs. Distributed optimization for multi-agent systems is an interesting topic that has attracted more and more attention due to its wide range of applications such as smart grids, sensor networks, and mobile manipulators. In distributed optimization, the goal is to optimize the global cost function, which is the sum of all local cost functions, each of which is known only by its own local agent. Distributed nonsmooth convex optimization for multi-agent systems based on proximal operators is developed to achieve distributed optimal consensus.
Les mer
Includes both linear and nonlinear multi-agent systems showing better performance with the proposed methods Introduces both distributed optimization and control methods for multi-agent systems Proposes practical and feasible methods for dynamics of multi-agent systems in general
Les mer
GPSR Compliance The European Union's (EU) General Product Safety Regulation (GPSR) is a set of rules that requires consumer products to be safe and our obligations to ensure this. If you have any concerns about our products you can contact us on ProductSafety@springernature.com. In case Publisher is established outside the EU, the EU authorized representative is: Springer Nature Customer Service Center GmbH Europaplatz 3 69115 Heidelberg, Germany ProductSafety@springernature.com
Les mer

Produktdetaljer

ISBN
9789819609499
Publisert
2025-03-22
Utgiver
Vendor
Springer Nature Switzerland AG
Høyde
235 mm
Bredde
155 mm
Aldersnivå
Research, P, 06
Språk
Product language
Engelsk
Format
Product format
Innbundet

Forfatter
Wang, Qing
Xin, Bin
Chen Jie

Om bidragsyterne

Qing Wang received the B.Eng. and Ph.D. degrees in control science and engineering from the School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing, China, in 2013 and 2018, respectively. She is currently a lecturer at the School of Automation, Beijing Institute of Technology. Her current research interests include multi-agent systems, nonlinear systems, intelligent control, and distributed optimization.

 

Bin Xin received the B.S. degree in information engineering and the Ph.D. degree in control science and engineering from the Beijing Institute of Technology, Beijing, China, in 2004 and 2012, respectively. He was an academic visitor at the Decision and Cognitive Sciences Research Centre at the University of Manchester from 2011 to 2012. He is currently a professor at the School of Automation, Beijing Institute of Technology. His current research interests include search and optimization, evolutionary computation, unmanned systems, and multi-agent systems.

 

Jie Chen received the B.S., M.S., and Ph.D. degrees in control theory and control engineering from the Beijing Institute of Technology, Beijing, China, in 1986, 1996, and 2001, respectively. He was the President of Tongji University, Shanghai, China, during 2018-2023. He is a Professor with the Control Science and Engineering, Beijing Institute of Technology and Tongji University, where he serves as the Director of the National Key Laboratory of Autonomous Intelligent Unmanned Systems (KAIUS). He is the academician of the Chinese Academy of Engineering and the fellow of the IEEE and IFAC. His current research interests include complex systems, multiagent systems, multiobjective optimization and decision, and constrained nonlinear control.

 

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