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Quantized adaptive decentralized control for interconnected nonlinear systems with actuator faults

Author

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  • Khan, Wakeel
  • Lin, Yan
  • Ullah Khan, Sarmad
  • Ullah, Nasim

Abstract

This paper studies quantized adaptive decentralized output feedback control technique for a class of interconnected nonlinear systems with quantized input and possible number of actuator failures up to infinity. A modified backstepping approach is proposed by the use of high-gain k-filters, hyperbolic tangent function property and bound-estimation approach to compensate for the effect of possible number of actuator failures up to infinity and input quantization. It is proved both mathematically and by simulation that, all the signals of the closed-loop system are globally bounded despite of input quantization and possible number of actuator failures up to infinity.

Suggested Citation

  • Khan, Wakeel & Lin, Yan & Ullah Khan, Sarmad & Ullah, Nasim, 2018. "Quantized adaptive decentralized control for interconnected nonlinear systems with actuator faults," Applied Mathematics and Computation, Elsevier, vol. 320(C), pages 175-189.
    • Handle: RePEc:eee:apmaco:v:320:y:2018:i:c:p:175-189
    DOI: 10.1016/j.amc.2017.09.011
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    References listed on IDEAS

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    1. Ran, Suzhen & Xue, Yanmei & Zheng, Bo-Chao & Wang, Zhenyou, 2017. "Quantized feedback fuzzy sliding mode control design via memory-based strategy," Applied Mathematics and Computation, Elsevier, vol. 298(C), pages 283-295.
    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:

    1. Ma, Jiali & Park, Ju H. & Xu, Shengyuan & Cui, Guozeng & Yang, Zhichun, 2020. "Command-filter-based adaptive tracking control for nonlinear systems with unknown input quantization and mismatching disturbances," Applied Mathematics and Computation, Elsevier, vol. 377(C).
    2. Wu, Li-Bing & Wang, Heng & He, Xi-Qin & Zhang, Da-Qing, 2018. "Decentralized adaptive fuzzy tracking control for a class of uncertain large-scale systems with actuator nonlinearities," Applied Mathematics and Computation, Elsevier, vol. 332(C), pages 390-405.
    3. Wu, Jing & Sun, Wei & Su, Shun-Feng & Xia, Jianwei, 2022. "Neural-based adaptive control for nonlinear systems with quantized input and the output constraint," Applied Mathematics and Computation, Elsevier, vol. 413(C).
    4. Xu, Yao & Chu, Chenyin & Li, Wenxue, 2018. "Quantized feedback control scheme on coupled systems with time delay and distributed delay: A finite-time inner synchronization analysis," Applied Mathematics and Computation, Elsevier, vol. 337(C), pages 315-328.
    5. Xiongfeng Deng & Yiqing Huang & Binzi Xu & Liang Tao, 2023. "Position and Attitude Tracking Finite-Time Adaptive Control for a VTOL Aircraft Using Global Fast Terminal Sliding Mode Control," Mathematics, MDPI, vol. 11(12), pages 1-22, June.
    6. Ma, Dazhong & Wang, Tianbiao & Zhang, Huaguang & Xie, Xiangpeng, 2021. "Adaptive fault-tolerant output regulation of linear systems with unknown dynamics and actuator faults," Applied Mathematics and Computation, Elsevier, vol. 402(C).

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