Cooperative Control of Multi-Agent Systems: An Optimal and Robust Perspective (Emerging Methodologies and Applications in Modelling, Identification and Control) - Softcover

Wang, Jianan; Wang, Chunyan; Xin, Ming; Ding, Zhengtao; Shan, Jiayuan

Softcover

ISBN 10: 0128201185 ISBN 13: 9780128201183

Publisher: Academic Press, 2020

Synopsis

Cooperative Control of Multi-Agent Systems: An Optimal and Robust Perspective reports and encourages technology transfer in the field of cooperative control of multi-agent systems. The book deals with UGVs, UAVs, UUVs and spacecraft, and more. It presents an extended exposition of the authors’ recent work on all aspects of multi-agent technology. Modelling and cooperative control of multi-agent systems are topics of great interest, across both academia (research and education) and industry (for real applications and end-users). Graduate students and researchers from a wide spectrum of specialties in electrical, mechanical or aerospace engineering fields will use this book as a key resource.

• Helps shape the reader's understanding of optimal and robust cooperative control design techniques for multi-agent systems
• Presents new theoretical control challenges and investigates unresolved/open problems
• Explores future research trends in multi-agent systems
• Offers a certain amount of analytical mathematics, practical numerical procedures, and actual implementations of some proposed approaches

About this title

About the Authors

Jianan Wang is currently an Associated Professor in the School of Aerospace Engineering at Beijing Institute of Technology, Beijing, China. He received his B.S. and M.S. in Control Science and Engineering from the Beijing Jiaotong University and Beijing Institute of Technology, Beijing, China, in 2004 and 2007, respectively. He received his Ph.D. in Aerospace Engineering at Mississippi State University, Starkville, MS, USA in 2011. His research interests include cooperative control of multiple dynamic systems, UAV formation control, obstacle/collision avoidance, trustworthy networked system, and estimation of sensor networks. He is a senior member of both IEEE and AIAA.

Chunyan Wang received the B.Eng. degree in automatic control from Dezhou University, Shandong, China, in 2006, the M.S. degree in control theory and control engineering from Soochow University, Jiangsu, China, in 2009, the M.Sc. degree in electrical and electronic engineering from the University of Greenwich, London, U.K., in 2012, and the Ph.D. degree in control systems from the University of Manchester, Manchester, U.K., in 2016. He is currently a Research Associate with the School of Electrical and Electronic Engineering, University of Manchester. His current research interests include cooperative control, robotics, and time-delay systems.

Ming Xin (SM’10) received the B.S. and M.S. degrees from the Nanjing University of Aeronautics and Astronautics, Nanjing, China, in 1993 and 1996, respectively, both in automatic control, and the Ph.D. degree in aerospace engineering from the Missouri University of Science and Technology, Rolla, MO, USA, in 2002. He is an Associate Professor with the Department of Mechanical and Aerospace Engineering, University of Missouri-Columbia, Columbia, MO. He has authored and coauthored more than 120 technical papers in his research areas. His research interests include optimization theory and applications, estimation/filtering and signal processing, and control of networked dynamic systems. Dr. Xin was the recipient of the U.S. National Science Foundation CAREER Award in 2009. He is an Associate Fellow of AIAA and a Senior Member of AAS.

Zhengtao Ding received B.Eng. degree from Tsinghua University, Beijing, China, and M.Sc. degree in systems and control, and the Ph.D. degree in control systems from the University of Manchester Institute of Science and Technology, Manchester, U.K. After working in Singapore for ten years, he joined the University of Manchester in 2003, where he is currently Professor of Control Systems and the Head of Control, Robotics and Communication Division. He is the author of the book: Nonlinear and Adaptive Control Systems (IET, 2013), a co-author of other two books, and has published over 300 research articles in control theory and applications. His research interests include nonlinear and adaptive control theory and their applications, more recently network-based control, distributed optimization and distributed learning, with applications to power systems and robotics. Prof. Ding has served as the Subject Chef Editor of Nonlinear Control for Frontiers, and Associate Editor for Scientific Reports, IEEE Transactions on Automatic Control, IEEE Transactions on Circuit and Systems II, IEEE Control Systems Letters, Journal of Franklin Institute, Transactions of the Institute of Measurement and Control, Control Theory and Technology, Unmanned Systems and several other journals. He is a member of IEEE Technical Committee on Nonlinear Systems and Control, IEEE Technical Committee on Intelligent Control, and IFAC Technical Committee on Adaptive and Learning Systems.

Jiayuan Shan received the B.S. degree from Huazhong University of Science and Technology in 1988, and the M.S. and Ph.D. degrees from Beijing Institute of Technology, in 1991 and 1999, respectively. He is currently a Professor at Beijing Institute of Technology. His research interests include guidance, navigation and control of the aircraft and hardware-in-the loop simulation. He is the Director of Department of Flight Vehicles Control and the Deputy Director of Flight Dynamics and Control Key Laboratory of Ministry of Education.

From the Back Cover

Cooperative Control of Multi-Agent Systems: An Optimal and Robust Perspective reports and encourages technology transfer in the field of cooperative control of multi-agent systems. The book deals with UGVs, UAVs, UUVs and spacecraft, and more. It presents an extended exposition of the authors’ recent work on all aspects of multi-agent technology. Modelling and cooperative control of multi-agent systems are topics of great interest, across both academia (research and education) and industry (for real applications and end-users). Graduate students and researchers from a wide spectrum of specialties in electrical, mechanical or aerospace engineering fields will use this book as a key resource.

Edition details

• Publisher: Academic Press
• Publication date: 2020
• Language: English
• ISBN 10: 0128201185
• ISBN 13: 9780128201183
• Binding: Paperback
• Edition number: 1
• Number of pages: 258