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A novel observer-based neural-network finite-time output control for high-order uncertain nonlinear systems

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  • Truong, Hoai Vu Anh
  • Phan, Van Du
  • Tran, Duc Thien
  • Ahn, Kyoung Kwan

Abstract

Due to the difficulty encountered in dealing with unstructured system dynamics with unmeasured system state variables, this paper presents a novel observer-based neural network finite-time output control strategy for general high-order nonlinear systems (HNSs). The suggested technique is performed based on the backstepping-like control (BSC) scheme with a hybrid nonlinear disturbance-state observer and norm estimation-based radial basis function neural network (RBFNN). This helps not only reduce the number of estimated parameters but also relax the restriction of using inequality when exploiting the norm estimation concept in a conventional way; thus, retaining the same properties of the original system. Therefore, an observer-based finite-time output feedback control is established to deal with the unstructured dynamical behaviors and satisfying the output tracking regulation with the semi-global practically finite-time stability (SGPFS) guaranteed for the closed-loop system. The effectiveness and workability of the proposed algorithm is verified by a numerical simulation on a specific practical application.

Suggested Citation

  • Truong, Hoai Vu Anh & Phan, Van Du & Tran, Duc Thien & Ahn, Kyoung Kwan, 2024. "A novel observer-based neural-network finite-time output control for high-order uncertain nonlinear systems," Applied Mathematics and Computation, Elsevier, vol. 475(C).
    • Handle: RePEc:eee:apmaco:v:475:y:2024:i:c:s0096300324001711
    DOI: 10.1016/j.amc.2024.128699
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    References listed on IDEAS

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    1. Wu, Dawei & Sun, Yonghui & Xia, Rongsheng & Lu, Shumin, 2022. "Improved Adaptive Fuzzy Control for Non-Strict Feedback Nonlinear Systems: a Dynamic Compensation System Approach," Applied Mathematics and Computation, Elsevier, vol. 435(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).
    3. Wang, Yingchun & Zhang, Jiaxin & Zhang, Huaguang & Xie, Xiangpeng, 2021. "Finite-time adaptive neural control for nonstrict-feedback stochastic nonlinear systems with input delay and output constraints," Applied Mathematics and Computation, Elsevier, vol. 393(C).
    4. Wu, Ziwen & Zhang, Tianping & Xia, Xiaonan & Hua, Yu, 2022. "Finite-time adaptive neural command filtered control for non-strict feedback uncertain multi-agent systems including prescribed performance and input nonlinearities," Applied Mathematics and Computation, Elsevier, vol. 421(C).
    5. Qing-Yuan Xu & Xiao-Dong Li, 2018. "Adaptive fuzzy ILC of nonlinear discrete-time systems with unknown dead zones and control directions," International Journal of Systems Science, Taylor & Francis Journals, vol. 49(9), pages 1878-1894, July.
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