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Finite-time adaptive neural control for nonstrict-feedback stochastic nonlinear systems with input delay and output constraints

Author

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  • Wang, Yingchun
  • Zhang, Jiaxin
  • Zhang, Huaguang
  • Xie, Xiangpeng

Abstract

This paper addresses a novel finite-time adaptive neural control (FTANC) problem for nonstrict-feedback stochastic nonlinear systems (NSFSNS), in which the input delay and output constrained problems are considered simultaneously. First, the Pade approximation technique is adopted to transform the delay input system into a delay-free one. Second, the stochastic nonlinear mapping technique is developed to solve the symmetric and asymmetric output constraints in the system. Then, the adaptive neural controller is designed based on backstepping technique, such that the closed-loop systems are semi-globally practical finite-time stable (SGPFTS) in probability, and the tracking error converges to a small neighborhood of the origin after a finite period of time. Two simulation examples show the effectiveness of the proposed approach.

Suggested Citation

  • 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).
    • Handle: RePEc:eee:apmaco:v:393:y:2021:i:c:s0096300320307098
    DOI: 10.1016/j.amc.2020.125756
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    References listed on IDEAS

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    1. Fang, Liandi & Ma, Li & Ding, Shihong & Zhao, Dean, 2019. "Finite-time stabilization for a class of high-order stochastic nonlinear systems with an output constraint," Applied Mathematics and Computation, Elsevier, vol. 358(C), pages 63-79.
    2. 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.
    3. Zhao, Nan-Nan & Wu, Li-Bing & Ouyang, Xin-Yu & Yan, Yan & Zhang, Rui-Yan, 2019. "Finite-time adaptive fuzzy tracking control for nonlinear systems with disturbances and dead-zone nonlinearities," Applied Mathematics and Computation, Elsevier, vol. 362(C), pages 1-1.
    4. Kwon, W. & Koo, Baeyoung & Lee, S.M., 2018. "Novel Lyapunov–Krasovskii functional with delay-dependent matrix for stability of time-varying delay systems," Applied Mathematics and Computation, Elsevier, vol. 320(C), pages 149-157.
    5. Xiao, Wenbin & Cao, Liang & Dong, Guowei & Zhou, Qi, 2019. "Adaptive fuzzy control for pure-feedback systems with full state constraints and unknown nonlinear dead zone," Applied Mathematics and Computation, Elsevier, vol. 343(C), pages 354-371.
    6. Hui Li & Fuqiang You & Fuli Wang & Shouping Guan, 2017. "Robust fast adaptive fault estimation and tolerant control for T-S fuzzy systems with interval time-varying delay," International Journal of Systems Science, Taylor & Francis Journals, vol. 48(8), pages 1708-1730, June.
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    Cited by:

    1. Jia, Jinping & Dai, Hao & Zhang, Fandi & Huang, Jianwen, 2022. "Global stabilization of low-order stochastic nonlinear systems with multiple time-varying delays by a continuous feedback control," Applied Mathematics and Computation, Elsevier, vol. 429(C).
    2. 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).
    3. 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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