Abstract
This paper deals with the problem of fault estimation observer design for T-S fuzzy nonlinear discrete-time descriptor systems in the finite frequency domain. First, a novel fault estimation observer for the augmented descriptor system is given. Based on Parseval's theorem and Lyapunov theory, the performance in the finite frequency domain is derived via time-domain method. Then, new sufficient conditions of admissibility and robust performance index for the dynamic error system are obtained as bilinear matrix inequalities. Meanwhile, an iterative linear matrix inequality algorithm is given to obtain the optimal solution. Finally, an example is given to demonstrate the effectiveness of our method.
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No potential conflict of interest was reported by the author(s).
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Notes on contributors
Yimin Liu
Yimin Liu received the M.S. degree in Pattern Recognition and Intelligent System from Beijing Institute of Technology, Beijing, China, in 2000. She joined the Wuhan University of Science and Technology in 1994, where she is currently an Associate Professor with the Department of Automation. Her current research interests include signal processing and machine learning, fault detection, and multi-agent systems.
Jianliang Chen
Jianliang Chen received the M.S. degree in signal and information processing from Harbin Engineering University, Harbin, China, in 2004 and the Ph.D. degree in control science and engineering from the Wuhan University of Science and Technology, Wuhan, China, in 2013. He was a Post-Doctoral Fellow with Shanghai Jiao Tong University, Shanghai, China. He joined the Wuhan University of Science and Technology in 2004, where he is currently an Associate Professor with the Department of Automation. His current research interests include robust and nonlinear control, fault detection, and multi-agent systems.
Hongjun Chu
Hongjun Chu received the M.S. degree in applied mathematics from Wenzhou University, Wenzhou, China, in 2009 and the Ph.D. degree in control science and engineering from Shanghai Jiao Tong University, Shanghai, China, in 2017.He is currently with the Institute of Advanced Technology, Nanjing University of Posts and Telecommunications, Nanjing, China. His current research interest includes distributed control and optimization and their application into smart grid.
Juan Li
Juan Li received the Ph.D. degree in control science and engineering from the Wuhan University of Science and Technology in 2016, now she is a lecturer in Wuhan University of Science and Technology. Her main research interests include image processing and machine learning.