Emergent Behavior Detection and Task Coordination for Multiagent Systems: a Distributed Estimation and Control Approach: 397 (Studies in Systems, Decision and Control, 397) [Hardcover] [Oct 24, 2021] Wang, Jing

This book addresses problems in the modeling, detection, and control of emergent behaviors and task coordination in multiagent systems. It presents a unified solution to such problems in terms of distributed estimation, distributed control, and optimization of interaction topologies and dynamics.

Emergent Behavior Detection and Task Coordination for Multiagent Systems is of interest to practicing engineers in areas such as robotics and cyber-physical systems, researchers in the field of systems, controls, and robotics, and senior undergraduate and graduate students.

Dr Jing Wang received his Ph.D. in control theory and control engineering in 1997 from Central South University, China. He was a Postdoctoral Research Fellow at the Institute of Computing Technology, Chinese Academy of Sciences, from 1997 to 1999 and at the Department of Electrical & Computer Engineering, National University of Singapore, from 1999 to 2002. From 2002 to 2007, he worked at the School of Electrical Engineering and Computer Science of the University of Central Florida as a Research Assistant Professor. From 2007 to 2014, he was with the Department of Computer Engineering & Computer Science, Bethune-Cookman University, Florida. Since August 2014, he has been working at the Department of Electrical and Computer Engineering, Bradley University, Illinois, and is currently an Associate Professor. He has published over 130 papers in peer-reviewed international journals and conferences and 4 book chapters, mainly in the areas of nonlinear control, cooperative control,adaptive control, robotics, and optimization. His research has been supported by governmental agencies (NSF, AFRL, AFOSR, NASA, DOT) and industry. Dr Wang is a Senior Member of the IEEE. His current research interests include cooperative control and robotics, distributed optimization and learning, nonlinear systems and control theory, and control applications in power converters and smart grids