Nonlinear Control of Dynamic Networks - Hill, David J.

. .

Résumé :
This text tackles newly arising theoretical and real-world challenges for stability analysis and control design. It first reviews the nonlinear small-gain theorems, and then presents novel cyclic-small-gain theorems for large-scale nonlinear dynamic networks, a cyclic-small-gain framework for nonlinear control with static or dynamic quantization, a combination of cyclic-small-gain and set-valued map designs for robust control of nonlinear uncertain systems subject to sensor noise, and a cyclic-small-gain result in directed graphs and distributed control of nonlinear multi-agent systems with fixed or dynamically changing topology....

Biographie:

Dr. Tengfei Liu holds a BE in automation and ME in control theory and engineering from the South China University of Technology, Guangzhou, as well as a Ph.D in engineering from the Australian National University, Acton, Canberra. He is a visiting assistant professor at the Polytechnic Institute of New York University, Brooklyn, USA. His current research interests include stability theory and robust nonlinear, quantized, and distributed control and their applications in mechanical, power, and transportation systems. Dr. Liu, with Prof. Zhong-Ping Jiang and Prof. David J. Hill, received the Guan Zhao-Zhi Best Paper Award at the 2011 Chinese Control Conference.

Prof. Zhong-Ping Jiang holds a BS in mathematics from the University of Wuhan, China...

Sommaire:

This text tackles newly arising theoretical and real-world challenges for stability analysis and control design. It first reviews the nonlinear small-gain theorems, and then presents novel cyclic-small-gain theorems for large-scale nonlinear dynamic networks, a cyclic-small-gain framework for nonlinear control with static or dynamic quantization, a combination of cyclic-small-gain and set-valued map designs for robust control of nonlinear uncertain systems subject to sensor noise, and a cyclic-small-gain result in directed graphs and distributed control of nonlinear multi-agent systems with fixed or dynamically changing topology.