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Adaptive Neural Network Sliding Mode Control for a Class of SISO Nonlinear Systems

Author

Listed:
  • Bin Li

    (School of Mathematics and Statistics, Qilu University of Technology, Shandong Academy of Sciences, Jinan 250353, China)

  • Jiahao Zhu

    (School of Mathematics and Statistics, Qilu University of Technology, Shandong Academy of Sciences, Jinan 250353, China)

  • Ranran Zhou

    (School of Mathematics and Statistics, Qilu University of Technology, Shandong Academy of Sciences, Jinan 250353, China)

  • Guoxing Wen

    (School of Mathematics and Statistics, Qilu University of Technology, Shandong Academy of Sciences, Jinan 250353, China
    College of Science, Binzhou University, Binzhou 256600, China)

Abstract

In this article, a sliding mode control (SMC) is proposed on the basis of an adaptive neural network (NN) for a class of Single-Input–Single-Output (SISO) nonlinear systems containing unknown dynamic functions. Since the control objective is to steer the system states to track the given reference signals, the SMC method is considered by employing the adaptive neural network (NN) strategy for dealing with the unknown dynamic problem. In order to compress the impaction coming from chattering phenomenon (which inherently exists in most SMC methods because of the discontinuous switching term), the boundary layer technique is considered. The basic design idea is to introduce a continuous proportional function to replace the discontinuous switching control term inside the boundary layer so that the chattering can be effectively alleviated. Finally, both Lyapunov theoretical analysis and computer numerical simulation are used to verify the effectiveness of the proposed SMC method.

Suggested Citation

  • Bin Li & Jiahao Zhu & Ranran Zhou & Guoxing Wen, 2022. "Adaptive Neural Network Sliding Mode Control for a Class of SISO Nonlinear Systems," Mathematics, MDPI, vol. 10(7), pages 1-12, April.
    • Handle: RePEc:gam:jmathe:v:10:y:2022:i:7:p:1182-:d:787043
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    References listed on IDEAS

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    1. Issaraporn Khonchaiyaphum & Nayika Samorn & Thongchai Botmart & Kanit Mukdasai, 2021. "Finite-Time Passivity Analysis of Neutral-Type Neural Networks with Mixed Time-Varying Delays," Mathematics, MDPI, vol. 9(24), pages 1-26, December.
    2. Kening Li & Jianyong Cao & Fan Yu, 2013. "Study on the Nonsingular Problem of Fractional-Order Terminal Sliding Mode Control," Mathematical Problems in Engineering, Hindawi, vol. 2013, pages 1-7, August.
    3. Igor Boiko, 2013. "Chattering in sliding mode control systems with boundary layer approximation of discontinuous control," International Journal of Systems Science, Taylor & Francis Journals, vol. 44(6), pages 1126-1133.
    4. Li, Zheng & Wang, Fang & Zhu, Ruitai, 2021. "Finite-time adaptive neural control of nonlinear systems with unknown output hysteresis," Applied Mathematics and Computation, Elsevier, vol. 403(C).
    5. Soares, Orlando & Gonçalves, Henrique & Martins, António & Carvalho, Adriano, 2010. "Nonlinear control of the doubly-fed induction generator in wind power systems," Renewable Energy, Elsevier, vol. 35(8), pages 1662-1670.
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