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Fuzzy-Based Adaptive Dynamic Surface Control for a Type of Uncertain Nonlinear System with Unknown Actuator Faults

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  • Xiongfeng Deng

    (School of Electrical Engineering, Anhui Polytechnic University, Wuhu 241000, China
    Key Laboratory of Advanced Perception and Intelligent Control of High-End Equipment, Ministry of Education, Anhui Polytechnic University, Wuhu 241000, China)

  • Jiakai Wang

    (College of Engineering & Science, University of Detroit Mercy, Detroit, MI 48221, USA)

Abstract

In this paper, the adaptive control problem of a type of uncertain nonlinear system is addressed. The system discussed includes unknown nonlinear functions, uncertain nonlinear dynamics, and unknown actuator faults. Based on the fuzzy logic systems and dynamic surface control technique, an adaptive fuzzy control law is designed to solve the tracking control problem. In control law design, fuzzy logic systems are utilized to approximate uncertain nonlinear functions, and with the help of the dynamic surface control technique, the problem of the “explosion of complexity” can be overcome. Through stability analysis, it is confirmed that all of the signals in the closed-loop system are semi-global bounded, and the convergence of the tracking error to the specified small neighborhood of the origin can be ensured by adjusting the control law parameters. Finally, the effectiveness of the proposed control law is verified by simulation examples.

Suggested Citation

  • Xiongfeng Deng & Jiakai Wang, 2022. "Fuzzy-Based Adaptive Dynamic Surface Control for a Type of Uncertain Nonlinear System with Unknown Actuator Faults," Mathematics, MDPI, vol. 10(10), pages 1-21, May.
    • Handle: RePEc:gam:jmathe:v:10:y:2022:i:10:p:1624-:d:812756
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    References listed on IDEAS

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    3. Wu, Li-Bing & Wang, Heng & He, Xi-Qin & Zhang, Da-Qing, 2018. "Decentralized adaptive fuzzy tracking control for a class of uncertain large-scale systems with actuator nonlinearities," Applied Mathematics and Computation, Elsevier, vol. 332(C), pages 390-405.
    4. Yoo, Sung Jin & Park, Bong Seok, 2021. "Quantized feedback control strategy for tracking performance guarantee of nonholonomic mobile robots with uncertain nonlinear dynamics," Applied Mathematics and Computation, Elsevier, vol. 407(C).
    5. Yingxue Hou & Shaocheng Tong & Yongming Li, 2016. "Adaptive fuzzy backstepping control for a class of switched nonlinear systems with actuator faults," International Journal of Systems Science, Taylor & Francis Journals, vol. 47(15), pages 3581-3590, November.
    6. Wang, Sanxia & Xia, Jianwei & Wang, Xueliang & Yang, Wenjing & Wang, Linqi, 2021. "Adaptive neural networks control for MIMO nonlinear systems with unmeasured states and unmodeled dynamics," Applied Mathematics and Computation, Elsevier, vol. 408(C).
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    Cited by:

    1. Xiongfeng Deng & Yiqing Huang & Lisheng Wei, 2022. "Adaptive Fuzzy Command Filtered Finite-Time Tracking Control for Uncertain Nonlinear Multi-Agent Systems with Unknown Input Saturation and Unknown Control Directions," Mathematics, MDPI, vol. 10(24), pages 1-22, December.
    2. Xiongfeng Deng & Yiming Yuan & Lisheng Wei & Binzi Xu & Liang Tao, 2022. "Adaptive Neural Tracking Control for Nonstrict-Feedback Nonlinear Systems with Unknown Control Gains via Dynamic Surface Control Method," Mathematics, MDPI, vol. 10(14), pages 1-13, July.

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