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Adaptive finite-time tracking control of strict-feedback nonlinear systems based on control law saturation

Author

Listed:
  • Gai, Yulin
  • Sun, Yue
  • Chen, Ming
  • Wu, Libing
  • Peng, Kaixiang
  • Wang, Huanqing

Abstract

For a class of strict-feedback nonlinear systems, an adaptive finite-time tracking control scheme is proposed in this study. First, a fuzzy state observer is introduced to estimate the unmeasurable states. The notable innovation of this design lies in the integration of differential explosion, control law saturation, fuzzy observers and finite-time control during the controller design process. Specifically, a novel smooth approximating function is introduced to enhance the accuracy of saturation computation. Simultaneously, the scheme compensates for the adverse effect of input saturation through virtual control law saturation. Finally, the numerical simulation and single-joint robotic arm system show that the proposed scheme not only has theoretical value, but also has significant practical significance.

Suggested Citation

  • Gai, Yulin & Sun, Yue & Chen, Ming & Wu, Libing & Peng, Kaixiang & Wang, Huanqing, 2026. "Adaptive finite-time tracking control of strict-feedback nonlinear systems based on control law saturation," Applied Mathematics and Computation, Elsevier, vol. 516(C).
    • Handle: RePEc:eee:apmaco:v:516:y:2026:i:c:s0096300325005697
    DOI: 10.1016/j.amc.2025.129844
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    References listed on IDEAS

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    1. Ge, Fudong & Chen, YangQuan, 2024. "Event-triggered control for boundary controlled time-fractional diffusion systems with spatially-varying coefficients," Applied Mathematics and Computation, Elsevier, vol. 478(C).
    2. Luo, Peng & Wu, Defeng & Yamashita, Andre S. & Feng, Na & Yang, Yang, 2024. "Observer-based fixed-time dynamic surface tracking control for autonomous surface vehicles under actuator constraints and denial-of-service attacks," Applied Mathematics and Computation, Elsevier, vol. 465(C).
    3. Yulin Li & Ben Niu & Guangdeng Zong & Jinfeng Zhao & Xudong Zhao, 2022. "Command filter-based adaptive neural finite-time control for stochastic nonlinear systems with time-varying full-state constraints and asymmetric input saturation," International Journal of Systems Science, Taylor & Francis Journals, vol. 53(1), pages 199-221, January.
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