Non-monotonic Approach to Robust H∞ Control of Multi-model Systems

Jiwei Wen received his Ph.D. degree in Control Science and Control Engineering from Jiangnan University, Wuxi, China, in 2011. From 2015 to 2016, he was a visiting scholar with the Department of Electrical and Computer Engineering, University of Auckland. Currently, he is an associate professor of School of Internet of Things Engineering, Jiangnan University, Wuxi, China. He is also a researcher in the Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education), Wuxi, China. His research interests include non-monotonic filtering and control approach, stochastic switched system, model predictive control and T-S fuzzy modelling and control. He has/had served as reviewer of a number of international journals. He is an Associate Editor of the International Journal of Sensors, Wireless Communications and Control. Alireza Nasiri holds a PhD degree from the University of Auckland, New Zealand. He is currently Assistant Professor in the Department of Electrical and Computer Engineering at Hormozgan University and vice president of Hormozgan Science and Technology Park, Iran. He received his B.Sc. and M.Sc. degrees in electrical engineering from the University of Tehran and Iran University of Science and Technology, respectively. His research interests are nonlinear control, fuzzy control, H8 control, active noise control and fault tolerant control. Sing Kiong Nguang is a professor with the Department of Electrical and Computer Engineering at the University of Auckland, Auckland, New Zealand. He received the B.E. (with first class honors) and the Ph.D. degree from the Department of Electrical and Computer Engineering at the University of Newcastle, Callaghan, Australia, in 1992 and 1995, respectively. He has published over 300 refereed journal and conference papers on nonlinear control design, nonlinear control systems, nonlinear time delay systems, nonlinear sampled-data systems, networked control systems, biomedical systems modelling, fuzzy modeling and control, biological systems modelling and control, and food and bio-product processing. He has/had served on the editorial board of a number of international journals. He is the Chief-Editor of the International Journal of Sensors, Wireless Communications and Control. Dhafer J. Almakhles received the B.E. degree from the department of Electrical Engineering of King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia, in 2006 and the Master’s (Hons.) degree from the University of Auckland, Auckland, New Zealand, in 2011. He completed his Ph.D. degree in 2016 from the University of Auckland. During his PhD, he managed to publish and submit high quality journal and conference papers and one book chapter. Currently, he is Assistant Professor at the Department of Communication and Networks Engineering and the coordinator of renewable energy research unit, Prince Sultan University, Riyadh, Saudi Arabia. His research interests include networked, event-triggered and quantized control systems, nonlinear control system, sliding mode control and real-time implementations on FPGA.

1. Introduction 2. Robust H- State Feedback Controller design of discrete-time T-S Fuzzy Systems: A Non-monotonic Approach 3. Robust H- Filtering of T-S Fuzzy Systems: A Non-monotonic Approach 4. Robust H- Output Feedback Control for T-S Fuzzy Systems: A Non-monotonic Approach 5. H- State feedback Control of Discrete-time Switched Systems via One-step ahead Lyapunov Function Approach 6. Stability, l2-Gain and Robust H- Control of Switched Systems via Multi-step ahead Non-monotonic Approach 7. H- filtering for Discrete-time Switched Systems via Multi-step ahead Non-monotonic Approach 8. H- Output feedback Control of Discrete-time Switched Systems via Multi-step ahead Non-monotonic Approach 9. Robust H- state feedback Control of Discrete-time Non-homogenous Markovian Jump Systems via Multi-step Lyapunov Function Approach 10. Robust H- filtering of Discrete-time Non-homogenous Markovian Jump Systems via Multi-step Lyapunov Function Approach 11. Conclusions