Fault-Tolerant Control for Time-Varying Delayed T-S Fuzzy Systems / Intelligent Control and Learning Systems Bd.9 (PDF)

Shaoxin Sun received her B.S. in control technology and instrumentation from Hebei University, Baoding, China, in 2014, her M.S. in control theory and control engineering from Northeastern University, Shenyang, China, in 2016, and her Ph.D. in control theory and control engineering from Northeastern University, Shenyang, China, in 2021. She currently serves as an assistant research fellow in the College of Automation at Chongqing University, Chongqing, China, where her research interests include fuzzy systems, stochastic/random systems, time-delay systems, fault estimation and fault-tolerant control.
Huaguang Zhang (M'03-SM'04-F'14) received his B.S. and M.S. in control engineering from the Northeast Dianli University of China, Jilin City, China, in 1982 and 1985, respectively, and his Ph.D. in thermal power engineering and automation from Southeast University, Nanjing, China, in 1991. He is a prolific author and inventor, having authored and co-authored over 280 journal and conference papers, six monographs, and co-invented 90 patents. His current research interests include fuzzy control, stochastic system control, neural networks-based control, nonlinear control, and their applications. Dr. Zhang has received numerous awards and honors, including the Outstanding Youth Science Foundation Award from the National Natural Science Foundation Committee of China in 2003, the IEEE Transactions on Neural Networks 2012 Outstanding Paper Award, and the Cheung Kong Scholar award from the Education Ministry of China in 2005. He currently serves as an associate editor for several journals, including Automatica, the IEEE Transactions on Neural Networks, the IEEE Transactions on Cybernetics, and Neurocomputing. He was an associate editor for the IEEE Transactions on Fuzzy Systems from 2008 to 2013 and currently serves as the E-letter chair of the IEEE CIS Society and the former chair of the Adaptive Dynamic Programming and Reinforcement Learning Technical Committee on IEEE