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Asymptotic tracking control for a class of uncertain nonlinear systems with output constraint

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  • Shi, Tianyu
  • Xiang, Zhengrong

Abstract

In this paper, we investigate the asymptotic tracking control for a class of strict-feedback nonlinear systems with unknown nonlinear functions and output constraint. The nonlinear transformation function-based system transformation approach is employed to convert the initial constrained system into an unconstrained one. To achieve the objective of asymptotic tracking, the tracking error is scaled by an exponential proportional function. Furthermore, to address the challenge of repetitive derivation of virtual control laws that occurs in the traditional design process of high-order backstepping methods, a first-order filter is applied. The designed control scheme guarantees that the system output will asymptotically track a predefined reference tracking trajectory while ensuring that the output constraint is not violated. Moreover, it is shown that the filter error will converge asymptotically to the origin. The effectiveness of the developed control strategy is verified through simulation results.

Suggested Citation

  • Shi, Tianyu & Xiang, Zhengrong, 2024. "Asymptotic tracking control for a class of uncertain nonlinear systems with output constraint," Applied Mathematics and Computation, Elsevier, vol. 478(C).
    • Handle: RePEc:eee:apmaco:v:478:y:2024:i:c:s0096300324003060
    DOI: 10.1016/j.amc.2024.128845
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    References listed on IDEAS

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    1. Wu, Meng & Wu, Li-Bing & Wang, Pu, 2024. "Event-triggered adaptive leaderless consensus control for nonlinear multi-agent systems with unknown dead-zones and output constraints," Applied Mathematics and Computation, Elsevier, vol. 469(C).
    2. Peng, Runlong & Guo, Rongwei & Zheng, Bin & Miao, Zhonghua & Zhou, Jin, 2024. "Neural network-based robust consensus tracking for uncertain networked Euler-Lagrange systems with time-varying delays and output constraints," Applied Mathematics and Computation, Elsevier, vol. 468(C).
    3. Zhang, Yan & Wang, Fang, 2019. "Adaptive neural control of non-strict feedback system with actuator failures and time-varying delays," Applied Mathematics and Computation, Elsevier, vol. 362(C), pages 1-1.
    4. Ma, Haoxiang & Xiong, Shixun & Fu, Zhumu & Tao, Fazhan & Ji, Baofeng, 2024. "High-order disturbance observer-based safe tracking control for a class of uncertain MIMO nonlinear systems with time-varying full state constraints," Applied Mathematics and Computation, Elsevier, vol. 466(C).
    5. Yi Qin & Fang Guo & Fujie Wang & Xing Li & Yaohua Hu, 2023. "Adaptive Control for an Aircraft Wing System with Hysteresis Nonlinearity," Mathematics, MDPI, vol. 11(18), pages 1-16, September.
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