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Predefined-time adaptive neural output-feedback control with filtered compensation for switched systems via event-triggered communication

Author

Listed:
  • Song, Yuhui
  • Wang, Huanqing
  • Liu, Xiaoping

Abstract

This study investigates the command filter-based adaptive neural predefined-time output-feedback control issue for nonlinear switched systems with arbitrary switching rule. Radial basis function neural networks (RBFNNs) are used to estimate uncertain nonlinearities, and a linear state observer is designed to estimate the unmeasurable states. Moreover, an event-triggered mechanism is utilized to alleviate the communication load. Specifically, a command filter technique is applied to tackle the computational complexity arising from the iterative differentiations of the indirect control functions. A command filter-based adaptive neural predefined-time output-feedback control strategy is formulated under the backstepping control framework, integrating the command filter control and the event-triggered mechanism. The developed control strategy guarantees that all the system signals are bounded and the tracking error converges to a little interval near origin within the predefined time. Finally, the simulation experiments reveal the validity of the devised control methodology.

Suggested Citation

  • Song, Yuhui & Wang, Huanqing & Liu, Xiaoping, 2026. "Predefined-time adaptive neural output-feedback control with filtered compensation for switched systems via event-triggered communication," Applied Mathematics and Computation, Elsevier, vol. 519(C).
    • Handle: RePEc:eee:apmaco:v:519:y:2026:i:c:s0096300325006587
    DOI: 10.1016/j.amc.2025.129933
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    References listed on IDEAS

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    1. Xu, Bo & Liang, Yanjun & Li, Yuan-Xin & Hou, Zhongsheng, 2022. "Adaptive command filtered fixed-time control of nonlinear systems with input quantization," Applied Mathematics and Computation, Elsevier, vol. 427(C).
    2. Xu, Ning & Zhao, Xudong & Zong, Guangdeng & Wang, Yuanqing, 2021. "Adaptive control design for uncertain switched nonstrict-feedback nonlinear systems to achieve asymptotic tracking performance," Applied Mathematics and Computation, Elsevier, vol. 408(C).
    3. Liu, Yanli & Hao, Li-Ying, 2024. "Adaptive tracking control for constrained nonlinear nonstrict-feedback switched stochastic systems with unknown control directions," Applied Mathematics and Computation, Elsevier, vol. 473(C).
    4. Yongchao Liu & Qidan Zhu, 2022. "Adaptive fuzzy asymptotic control for switched nonlinear systems with state constraints," International Journal of Systems Science, Taylor & Francis Journals, vol. 53(5), pages 922-933, April.
    5. Xia, Meizhen & Liu, Zhucheng & Zhang, Tianping, 2023. "Distributed adaptive cooperative control via command filters for multi-agent systems including input unmodeled dynamics and sensor faults," Applied Mathematics and Computation, Elsevier, vol. 457(C).
    Full references (including those not matched with items on IDEAS)

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