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Adaptive H-infinity SMC-based Model Reference Tracker for Uncertain Nonlinear Systems with Input Nonlinearity

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Abstract

This paper presents a novel robust H∞ model reference adaptive tracker (MRAT) for a class of nonlinear systems with input nonlinearities, uncertainties, and mismatched disturbances. Since the bounds of input nonlinearities and uncertainties are unknown, a new adaptive controller is proposed to solve these problems. Because the proposed adaptive laws are with convergence, the adaptive gains estimated can avoid overestimation. Furthermore, the sliding mode control (SMC) is implemented integrated with a smooth function, then the undesirable chattering phenomenon is reduced. Finally, the proposed tracking controller can process the undesirable effects of external disturbances and promote the tracking performance even subjected to the unknown input nonlinearity. The numerical simulation results demonstrate the robustness and validity of the proposed tracking controller.

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Authors and Affiliations

  1. Department of Electrical Engineering, National Cheng-Kung University, Tainan City, Taiwan

    Jiunn-Shiou Fang, Jason Sheng-Hong Tsai & Shu-Mei Guo

  2. Department of Electronic Engineering, National Chin-Yi University of Technology, Taichung City, Taiwan

    Jun-Juh Yan

Authors
  1. Jiunn-Shiou Fang
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  2. Jason Sheng-Hong Tsai
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  3. Jun-Juh Yan
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  4. Shu-Mei Guo
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Corresponding author

Correspondence to Jun-Juh Yan.

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Recommended by Associate Editor Wenhai Qi under the direction of Editor Hamid Reza Karimi. This work was supported by the Ministry of Science and Technology of R.O.C [MOST 108-2221-E-006-213-MY3] and [MOST-109-2221-E-167-017].

Jiunn-Shiou Fang received his B.S. and M.S. degrees from the National Changhua University of Education, Taiwan, and a Ph.D. degree in electrical engineering from Cheng-Kung University, Taiwan, respectively. His research interests include nonlinear control and intelligent algorithms.

Jason Sheng-Hong Tsai received both his M.S. and Ph.D. degrees in electrical engineering from University of Houston, Texas, U.S.A. in 1985 and 1988, respectively. Since August 1988, he has been an associate professor in the Department of Electrical Engineering at National Cheng-Kung University, Taiwan, R.O.C. He has been a full professor since August 1992 and a distinguished professor since Aug. 2002. His research interests include state-space self-tuning control, chaotic system control, partial differential system control, numerical analysis, and robotics. He was (Executive) Editor for Science Development, published by National Science Council, R.O.C., Editor for Journal of the Chinese Institute of Electrical Engineering during, Associate Editor for International Journal of Systems Science, and Associate Editor for The Journal of The Franklin Institute.

Jun-Juh Yan received his M.S. degree in electrical engineering from National Central University, Taiwan in 1992 and his B.S. and Ph.D. degrees in electrical engineering from the National Cheng Kung University, Taiwan, in 1987 and 1998, respectively. At present, he is a Professor in the Department of Electronic Engineering, National Chin-Yi University of Technology, Taichung, Taiwan. His main research interests are in the area of multi-robot dynamic systems, chaotic systems, neural networks, variable-structure control systems, and adaptive control.

Shu-Mei Guo received her M.S. degree from the Department of Computer and Information Science, New Jersey Institute of Technology, Newark, in 1987, and a Ph.D. degree in computer and systems engineering from University of Houston, Houston, TX, in May 2000. Since June 2000, she has been an assistant professor with the Department of Computer System and Information Engineering, National Cheng-Kung University, Tainan, Taiwan, and since August 2010, she has been a full professor. Her research interests include various applications on evolutionary programming, chaos systems, Kalman filtering, fuzzy methodology, neural network, sampled-data systems, and computer and systems engineering.

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Fang, JS., Tsai, J.SH., Yan, JJ. et al. Adaptive H-infinity SMC-based Model Reference Tracker for Uncertain Nonlinear Systems with Input Nonlinearity. Int. J. Control Autom. Syst. 19, 1560–1569 (2021). https://doi.org/10.1007/s12555-019-0967-7

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  • DOI: https://doi.org/10.1007/s12555-019-0967-7

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