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Observer-based adaptive control for nonlinear input-delay systems with unknown control directions

Author

Listed:
  • Jiali Ma
  • Guangming Zhuang
  • Guozeng Cui
  • Jiaqi Wang

Abstract

This paper investigates the problem of adaptive control for strict-feedback nonlinear systems with input delay and unknown control directions. The Nussbaum function is utilised to deal with the unknown control directions and a novel compensation system is introduced to handle the time-varying input delay. By using neural network(NN) approximation and backstepping approaches, an adaptive NN controller is designed which can guarantee the semi-global boundedness of all the signals in the closed-loop system. Two simulation examples are also given to illustrate the effectiveness of the proposed method.

Suggested Citation

  • Jiali Ma & Guangming Zhuang & Guozeng Cui & Jiaqi Wang, 2019. "Observer-based adaptive control for nonlinear input-delay systems with unknown control directions," International Journal of Systems Science, Taylor & Francis Journals, vol. 50(8), pages 1543-1555, June.
    • Handle: RePEc:taf:tsysxx:v:50:y:2019:i:8:p:1543-1555
    DOI: 10.1080/00207721.2019.1616848
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    Cited by:

    1. Zhang, Zhipeng & Wang, Huimin, 2022. "Resilient decentralized adaptive tracking control for nonlinear interconnected systems with unknown control directions against DoS attacks," Applied Mathematics and Computation, Elsevier, vol. 415(C).
    2. 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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