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Adaptive fuzzy guaranteed performance control for uncertain nonlinear systems with event-triggered input

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  • Xi, Changjiang
  • Dong, Jiuxiang

Abstract

This paper investigates the issue of event-triggered adaptive tracking control for a class of nonlinear systems with unmeasurable states and uncertain nonlinearities. A state observer based on fuzzy logic systems (FLSs) is first established for further stability analysis. Under the framework of backstepping technique, a novel adaptive backstepping control scheme is proposed, where the controller updates are event-driven to decrease the communication burden between the plant and the controller. Differing from the existing results for periodic event-triggered control (ETC), the proposed event-triggered strategy is aperiodic, which depends on the measurement errors with respect to fixed threshold and the magnitude of control signal. Especially, it should be mentioned that the discontinuous control signals in ETC might bring poor transient performance. Therefore, the prescribed performance bounds (PPBs) method with barrier Lyapunov function is utilized to balance the system performance and the number of triggering events. Finally, it is proved that all closed-loop signals can converge to a desired compact set and the output tracking error is within the specified bounds. Simulation example illustrates the effectiveness of the proposed control scheme.

Suggested Citation

  • Xi, Changjiang & Dong, Jiuxiang, 2019. "Adaptive fuzzy guaranteed performance control for uncertain nonlinear systems with event-triggered input," Applied Mathematics and Computation, Elsevier, vol. 363(C), pages 1-1.
    • Handle: RePEc:eee:apmaco:v:363:y:2019:i:c:43
    DOI: 10.1016/j.amc.2019.124604
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    References listed on IDEAS

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    1. Li, Junmin & Yue, Hongyun, 2015. "Adaptive fuzzy tracking control for stochastic nonlinear systems with unknown time-varying delays," Applied Mathematics and Computation, Elsevier, vol. 256(C), pages 514-528.
    2. Xi, Changjiang & Zhai, Ding & Li, Xiaojian & Zhang, Qingling, 2017. "Decentralized adaptive delay-dependent neural network control for a class of large-scale interconnected nonlinear systems," Applied Mathematics and Computation, Elsevier, vol. 311(C), pages 148-163.
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    Cited by:

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    2. Xi, Changjiang & Dong, Jiuxiang, 2021. "Adaptive asymptotic tracking control of uncertain nonlinear time-delay systems depended on delay estimation information," Applied Mathematics and Computation, Elsevier, vol. 391(C).
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    6. Zhou, Zepeng & Zhu, Fanglai & Xu, Dezhi & Guo, Shenghui & Zhao, Younan, 2022. "Attack resilient control for vehicle platoon system with full states constraint under actuator faulty scenario," Applied Mathematics and Computation, Elsevier, vol. 419(C).
    7. Ju, Xinxu & Jia, Xianglei & Shi, Xiaocheng & Yu, Shan’en, 2022. "Adaptive output feedback event-triggered tracking control for nonlinear systems with unknown control coefficient," Applied Mathematics and Computation, Elsevier, vol. 432(C).
    8. Liu, Hui & Li, Xiaohua, 2023. "A prescribed-performance-based adaptive finite-time tracking control scheme circumventing the dependence on the system initial condition," Applied Mathematics and Computation, Elsevier, vol. 448(C).
    9. Yue, Xiaohui & Shao, Xingling & Li, Jie, 2021. "Prescribed chattering reduction control for quadrotors using aperiodic signal updating," Applied Mathematics and Computation, Elsevier, vol. 405(C).
    10. Yuan, Manman & Zhai, Junyong & Ye, Hui, 2022. "Adaptive output feedback control for a class of switched stochastic nonlinear systems via an event-triggered strategy," Applied Mathematics and Computation, Elsevier, vol. 422(C).

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