Cooperative Control of Nonlinear Multiagent Systems Passivity-Based and Non-Passivity-Based Approaches

Cooperative Control for Nonlinear Multiagent Systems: Passivity-Based and Non-Passivity-Based Approaches focuses on the cooperative control of nonlinear multiagent systems containing passivity-based or non-passivity-based consensus, lag consensus, and formation control of multiagent systems. The book provides professional and convenient guidance for those who want to know basic knowledge, advancements, and processes for designing and analyzing cooperative control for nonlinear multiagent systems.

Currently, there are a lack of reference titles that systematically introduce students, researchers, and technologists to the backgrounds, developments, and designs protocols for cooperative control (contains passivity-based or not passivity-based consensus, lag consensus, formation control) of nonlinear multiagent systems.

Jin Liang Wang (Senior Member, IEEE) received a Ph.D. degree in control theory and control engineering from the School of Automation Science and Electrical Engineering, Beihang University, China, in January 2014. From 2014 to 2020, he has lectured and served as professor at the School of Computer Science and Technology, Tiangong University, China. He has authored 3 English academic monographs and over 40 SCI-indexed journal papers, which have been cited more than 1500 times. 11 first author papers were recognized by the ESI Highly Cited Papers, and 1 first author paper was selected as the ESI Hot Paper. His current research interests include synchronization, passivity, consensus, formation control, fractional-order systems, complex networks, coupled reaction-diffusion neural networks, and multiagent systems. Prof. Wang was a Managing Guest Editor for the Special Issue on Dynamical Behaviors of Coupled Neural Networks with Reaction-Diffusion Terms: Analysis, Control and Applications in Neurocomputing. He also serves as an Associate Editor for Neurocomputing, the International Journal of Adaptive Control and Signal Processing, and Complex & Intelligent Systems.
Tingwen Huang (Fellow, IEEE) received his B.S. degree in Mathematics from Southwest Normal University, China, in 1990, a M.S. degree in Applied Mathematics from Sichuan University, China, in 1993, and a Ph.D. degree in Mathematics from Texas A&M University, College Station, USA, in 2002. He was a Lecturer with Jiangsu University, China, from 1994 to 1998, and a Visiting Assistant Professor with Texas A&M University, USA in 2003. He served as Assistant Professor and Associate Professor at Texas A&M University at Qatar, Qatar from 2003 to 2013, he has served as a Professor there since 2013. His current research interests include neural networks, complex networks, chaos and dynamics of systems, and operator semigroups and their applications.