Finite-Time Fuzzy Sliding Mode Control for Nonlinear Descriptor Systems

Zhixiong Zhong; Xingyi Wang; Hak-Keung Lam

doi:10.1109/JAS.2021.1004024

Volume 8 Issue 6

Jun. 2021

IEEE/CAA Journal of Automatica Sinica

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Article Navigation > IEEE/CAA Journal of Automatica Sinica > 2021 > 8(6): 1141-1152

Z. X. Zhong, X. Y. Wang, and H. Lam, "Finite-Time Fuzzy Sliding Mode Control for Nonlinear Descriptor Systems," IEEE/CAA J. Autom. Sinica, vol. 8, no. 6, pp. 1141-1152, Jun. 2021. doi: 10.1109/JAS.2021.1004024

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Z. X. Zhong, X. Y. Wang, and H. Lam, "Finite-Time Fuzzy Sliding Mode Control for Nonlinear Descriptor Systems," IEEE/CAA J. Autom. Sinica, vol. 8, no. 6, pp. 1141-1152, Jun. 2021. doi: 10.1109/JAS.2021.1004024

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Finite-Time Fuzzy Sliding Mode Control for Nonlinear Descriptor Systems

doi: 10.1109/JAS.2021.1004024

1.
Key Laboratory of Information Processing and Intelligent Control, Minjiang University, Fuzhou 350121, China
2.
College of Mechanical and Electronic Engineering, Fujian Agriculture and Forestry University, Fuzhou 350108, China
3.
Department of Engineering, King’s College London, London, WC2R 2LS, United Kingdom

Funds: This work was supported in part by the Central Government Drects Special Funds for Scientific and Technological Development of China (2019L3009), and Natural Science Foundation of Fujian Province of China (2020J02045)

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Author Bio:
Zhixiong Zhong (M’18) received the B.S. degree in mechatronics from Fuzhou University in 2008, and the M.S. degree in control theory and control engineering from Fuzhou University in 2012. In 2013 he was a visiting student with the Department of Mechanical Engineering, University of Victoria, Canada. In 2015 he received the Ph.D. degree in the Research Institute of Intelligent Control and Systems, Harbin Institute of Technology and jointed in the School of Computer and Control Engineering, Minjiang University in 2018. He is currently a Professor in Minjiang University. He has published more than 40 papers in journals, conferences, and authored two books: Modeling, Control, Estimation, and Optimization for Microgrids: A Fuzzy-Model-Based Method (CRC, 2019) and Large-Scale Fuzzy Interconnected Control Systems Design and Analysis (IGI Global, 2017). His research interests include fuzzy control, robust filtering, and large-scale control

Xingyi Wang received M.S. degree in control theory and control engineering from Fuzhou University in 2011. She is currently an Associate Professor in Minjiang University, and working toward the Ph.D. degree at the College of Mechanical and Electronic Engineering, Fujian Agriculture and Forestry University. Her research interests include fuzzy logic systems, control with neural networks

Hak-Keung Lam (M’98–SM’12–F’20) received the B.Eng. (Hons.) and Ph.D. degrees from the Department of Electronic and Information Engineering, The Hong Kong Polytechnic University, Hong Kong, China, in 1995 and 2000, respectively. During the period of 2000 and 2005, he worked with the Department of Electronic and Information Engineering at The Hong Kong Polytechnic University as Post-Doctoral Fellow and Research Fellow, respectively. He joined as a Lecturer at King’s College London in 2005 and is currently a Reader. His current research interests include intelligent control systems and computational intelligence. He has served as a program committee member and international advisory board member for various international conferences and a reviewer for various books, international journals and international conferences. He is an Associate Editor for IEEE Transactions on Fuzzy Systems, IEEE Transactions on Circuits and Systems II: Express Briefs, IET Control Theory and Applications, International Journal of Fuzzy Systems, Neurocomputing, and Nonlinear Dynamics; and Guest Editor for a number of international journals, and is in the editorial board of for a number of international journals. He was named as Highly Cited Researcher and is an IEEE Fellow. He is the coeditor for two edited volumes: Control of Chaotic Nonlinear Circuits (World Scientific, 2009) and Computational Intelligence and Its Applications (World Scientific, 2012), and the coauthor of the monographs: Stability Analysis of Fuzzy-Model-Based Control Systems (Springer, 2011), Polynomial Fuzzy Model Based Control Systems (Springer, 2016), and Analysis and Synthesis for Interval Type-2 Fuzzy-Model-Based Systems (Springer, 2016)
Corresponding author: Xingyi Wang, e-mail: xingyiwang2019@126.com
Received Date: 2020-02-05
Revised Date: 2021-01-10
Accepted Date: 2021-03-14

Available Online: 2021-03-26

Abstract

Abstract

This article addresses the finite-time boundedness (FTB) problem for nonlinear descriptor systems. Firstly, the nonlinear descriptor system is represented by the Takagi-Sugeno (T-S) model, where fuzzy representation is assumed to be appearing not only in both the state and input matrices but also in the derivative matrix. By using a descriptor redundancy approach, the fuzzy representation in the derivative matrix is reformulated into a linear one. Then, we introduce a fuzzy sliding mode control (FSMC) law, which ensures the finite-time boundedness (FTB) of closed-loop fuzzy control systems over the reaching phase and sliding motion phase. Moreover, by further employing the descriptor redundancy representation, the sufficient condition for designing FSMC law, which ensures the FTB of the closed-loop control systems over the entire finite-time interval, is derived in terms of linear matrix inequalities (LMIs). Finally, a simulation study with control of a photovoltaic (PV) nonlinear system is given to show the effectiveness of the proposed method.
- Finite-time boundedness (FTB),
- fuzzy sliding mode control (FSMC),
- Takagi-Sugeno (T-S) fuzzy descriptor system

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By using a descriptor redundancy approach, the fuzzy representation in the derivative matrix of system is reformulated into the linear one.
For a specified time interval, partition with transient dynamics of sliding mode control into two subintervals: Reaching phase and sliding motion phase.
Based on the Lyapunov function in the descriptor system domain, the design of FSMC Law is derived in terms of LMIs.

Finite-Time Fuzzy Sliding Mode Control for Nonlinear Descriptor Systems

doi: 10.1109/JAS.2021.1004024

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