Resilient Cooperative Control and Optimization of Multi-Agent Systems (Advanced Topics in Biomaterials) - Softcover

Feng PhD, Zhi; Dong PhD, Xiwang; Hu PhD, Guoqiang; Lyu PhD, Jinhu

Softcover

ISBN 10: 0443329885 ISBN 13: 9780443329883

Publisher: Academic Press, 2025

Synopsis

Resilient Cooperative Control and Optimization of Multi-Agent Systems addresses various resilient cooperative control and optimization problems of multi-agent systems that are vulnerable to physical failure and cyber attacks and consist of multiple decision-making agents that interact in a shared environment to achieve common or conflicting goals. Critical infrastructures, such as smart grids, wireless sensor network, multi-robot system, etc., are typical examples of multi-agent systems that consist of the large-scale physical processes which are monitored and controlled over a set of communication networks and computers.

• Presents solutions to different resilient cooperative control and optimization problems of multi-agent systems
• Includes a wealth of examples on attack-resilient consensus control, time-varying formation tracking control, distributed optimization and distributed Nash equilibrium game-seeking
• Shows, in detail, the practicalities of how to develop an attack-resilient cooperative control and optimization framework

About this title

About the Authors

Dr Zhi Feng joined the School of Automation Science and Electrical Engineering, Beihang University, Beijing, in2022, where he is currently an associate professor. He received the Ph.D. degree in Control Science and Engineering from Nanyang Technological University, Singapore, in 2017, where he worked as a research fellow from 2018 to 2020; he was a Wallenberg-NTU Presidential Postdoctoral Fellow from 2020 to 2022. His research interests include distributed control, optimization, and game theory with applications to multi-robot systems

Professor Xiwang Dong joined the School of Automation Science and Electrical Engineering, Beihang University, Beijing, in 2014, where he is currently a Professor, and also an Associate Dean with the Institute of Artificial Intelligence. He received the B.E. degree in Automation from Chongqing University, Chongqing, China, in 2009, and the Ph.D. degree in Control Science and Engineering from Tsinghua University, Beijing, China, in 2014. From 2014 to 2015, he was also a Research Fellow with the School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore. His research interests include formation control, and containment control of swarm systems with applications to UAV systems

Professor Guoqiang Hu joined the School of Electrical and Electronic Engineering, Nanyang Technological University in Singapore in 2011, where he is currently a full professor. He received a B.Eng. in Automation from the University of Science and Technology of China in 2002, M.Phil. in Automation and Computer-Aided Engineering from the Chinese University of Hong Kong in 2004, and Ph.D. in Mechanical Engineering from University of Florida in 2007. His research interests include optimization and control, distributed optimization and game theory, and data science, with applications to multi-robot systems and smart city systems

Professor Jinhu Lyu received his Ph.D. in applied mathematics from the Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, China, in 2002. He was a Professor with RMIT University, Melbourne, VIC, Australia, and a Visiting Fellow with Princeton University, Princeton, NJ, USA. Currently, he is the Dean with the School of Automation Science and Electrical Engineering, Beihang University, Beijing, China. He is also a Professor with the Academy of Mathematics and Systems Science, Chinese Academy of Sciences. His current research interests include complex networks, industrial Internet, network dynamics and cooperation control

From the Back Cover

Critical infrastructures, such as smart grids, wireless sensor network, multi-robot system, etc., are typical examples of multi-agent systems that consist of the large-scale physical processes which are monitored and controlled over a set of communication networks and computers. A multi-agent system consists of multiple decision-making agents which interact in a shared environment to achieve common or conflicting goals. Resilient Cooperative Control and Optimization of Multi-Agent Systems addresses various resilient cooperative control and optimization problems of multi-agent systems, which are vulnerable to physical failure and cyber attacks.

Edition details

• Publisher: Academic Press
• Publication date: 2025
• Language: English
• ISBN 10: 0443329885
• ISBN 13: 9780443329883
• Binding: Paperback
• Edition number: 1
• Number of pages: 336