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Adaptive neural networks control for MIMO nonlinear systems with unmeasured states and unmodeled dynamics

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  • Wang, Sanxia
  • Xia, Jianwei
  • Wang, Xueliang
  • Yang, Wenjing
  • Wang, Linqi

Abstract

In this paper, an adaptive neural networks control scheme is developed for a class of multi input and multi output uncertain nonlinear systems with unmeasured states and unmodeled dynamics. In the control scheme, a dynamic signal is used to deal with the unmodeled dynamics and a neural observer is designed to estimate the unmeasured states. Meanwhile, the neural networks are used to estimate the combinational unknown nonlinear function at each step of backstepping process. It is proved that all signals of the closed-loop system are semi global uniformly ultimately bounded (SGUUB). Finally, a simulation example is provided to show the effectiveness of the proposed control method.

Suggested Citation

  • 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).
    • Handle: RePEc:eee:apmaco:v:408:y:2021:i:c:s0096300321004586
    DOI: 10.1016/j.amc.2021.126369
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    References listed on IDEAS

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    1. Min, Huifang & Xu, Shengyuan & Yu, Xin & Fei, Shumin & Cui, Guozeng, 2020. "Adaptive Tracking Control for Stochastic Nonlinear Systems with Full-State Constraints and Unknown Covariance Noise," Applied Mathematics and Computation, Elsevier, vol. 385(C).
    2. Jiali Ma & Guangming Zhuang & Guozeng Cui & Jiaqi Wang, 2019. "Observer-based adaptive control for nonlinear input-delay systems with unknown control directions," International Journal of Systems Science, Taylor & Francis Journals, vol. 50(8), pages 1543-1555, June.
    3. Tingting Gao & Jiangshuai Huang & Yong Zhou, 2018. "Adaptive consensus control of nonlinear systems with unknown control directions," International Journal of Systems Science, Taylor & Francis Journals, vol. 49(9), pages 1908-1917, July.
    4. Baoyu Huo & Shaocheng Tong & Yongming Li, 2013. "Adaptive fuzzy fault-tolerant output feedback control of uncertain nonlinear systems with actuator faults," International Journal of Systems Science, Taylor & Francis Journals, vol. 44(12), pages 2365-2376.
    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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    Cited by:

    1. 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).
    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. Chen, Xiang & Li, Shi & Wang, Ronghao & Xiang, Zhengrong, 2023. "Event-Triggered output feedback adaptive control for nonlinear switched interconnected systems with unknown control coefficients," Applied Mathematics and Computation, Elsevier, vol. 445(C).
    4. Xiongfeng Deng & Jiakai Wang, 2022. "Fuzzy-Based Adaptive Dynamic Surface Control for a Type of Uncertain Nonlinear System with Unknown Actuator Faults," Mathematics, MDPI, vol. 10(10), pages 1-21, May.

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