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Part One - About Cooperative Control
Part Two - Optimal Cooperative Control
3. Optimal consensus control of multiple integrator systems
4. Optimal cooperative tracking and flocking of multi-agent systems
5. Optimal formation control of multiple UAVs
6. Optimal coverage control of multi-robot systems
Part Three - Robust Cooperative Control
7. Robust consensus control of multi-agent systems with input delay
8. Robust consensus control of multi-agent systems with disturbance rejection
9. Robust consensus control nonlinear p-order integrator systems
10. Robust cooperative control of networked negative-imaginary systems
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
Researchers, graduate students, engineers and practitioners in Electrical, Mechanical, and Aerospace Engineering; experts and industrial control engineers
- No. of pages:
- © Academic Press 2020
- 26th March 2020
- Academic Press
- Paperback ISBN:
- eBook ISBN:
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.
School of Aerospace Engineering at Beijing Institute of Technology, Beijing, China.
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.
School of Electrical and Electronic Engineering, University of Manchester.
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.
Department of Mechanical and Aerospace Engineering, University of Missouri-Columbia, Columbia, MO
Zhengtao Ding (SM’03) received the B.Eng. degree from Tsinghua University, Beijing, China, and the 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. He was a Lecturer with Ngee Ann Polytechnic, Singapore, for ten years. In 2003, he joined the University of Manchester, Manchester, U.K., where he is currently the Professor of Control Systems with the School of Electrical and Electronic Engineering. He has authored the book entitled Nonlinear and Adaptive Control Systems (IET, 2013) and a number of journal papers. His current research interests include nonlinear and adaptive control theory and their applications. Prof. Ding serves as an Associate Editor for the IEEE TRANSACTIONS ON AUTOMATIC CONTROL, the IEEE CONTROL SYSTEMS LETTERS, Transactions of the Institute of Measurement and Control, Control Theory and Technology, Mathematical Problems in Engineering, Unmanned Systems, and the International Journal of Automation and Computing.
University of Manchester, Manchester, U.K
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.
Beijing Institute of Technology
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