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Quantized feedback fuzzy sliding mode control design via memory-based strategy

Author

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  • Ran, Suzhen
  • Xue, Yanmei
  • Zheng, Bo-Chao
  • Wang, Zhenyou

Abstract

This paper is concerned with the sliding mode control (SMC) design for a class of Takagi–Sugeno (T–S) fuzzy nonlinear systems subject to model uncertainties and input quantization mismatch. A novel memory-based sliding surface is presented which includes not only the current states but also the past state information of the systems. Sufficient conditions for the design of the switching gains are given via linear matrix inequality(LMI) technique, and then the reaching conditions of the sliding surface is constructed to ensure the reachability of the sliding manifold. Furthermore, an adaptive neuro-fuzzy inference system(ANFIS) is introduced for reducing the high-frequency chattering induced by the signum function term in the sliding mode control. The effectiveness of the proposed methodology is illustrated by Matlab simulations.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:apmaco:v:298:y:2017:i:c:p:283-295
    DOI: 10.1016/j.amc.2016.11.011
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    References listed on IDEAS

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    1. Zhai, Ding & Lu, An-Yang & Dong, Jiuxiang & Zhang, Qing-Ling, 2017. "Stability analysis and state feedback control of continuous-time T–S fuzzy systems via anew switched fuzzy Lyapunov function approach," Applied Mathematics and Computation, Elsevier, vol. 293(C), pages 586-599.
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    4. Chang, Xiao-Heng & Xiong, Jun & Park, Ju H., 2016. "Fuzzy robust dynamic output feedback control of nonlinear systems with linear fractional parametric uncertainties," Applied Mathematics and Computation, Elsevier, vol. 291(C), pages 213-225.
    5. Yuanyuan Zou & Yugang Niu & Bei Chen & Tinggang Jia, 2013. "Networked predictive control of constrained linear systems with input quantisation," International Journal of Systems Science, Taylor & Francis Journals, vol. 44(10), pages 1970-1982.
    6. Zhou, Qi & Yao, Deyin & Wang, Jiahui & Wu, Chengwei, 2016. "Robust control of uncertain semi-Markovian jump systems using sliding mode control method," Applied Mathematics and Computation, Elsevier, vol. 286(C), pages 72-87.
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    Cited by:

    1. Xue, Yanmei & Zheng, Bo-Chao & Li, Tao & Li, Yuanlu, 2017. "Robust adaptive state feedback sliding-mode control of memristor-based Chua’s systems with input nonlinearity," Applied Mathematics and Computation, Elsevier, vol. 314(C), pages 142-153.
    2. Wang, Bo & Cheng, Jun & Zhou, Xia, 2020. "A multiple hierarchical structure strategy to quantized control of Markovian switching systems," Applied Mathematics and Computation, Elsevier, vol. 373(C).
    3. Xue, Yanmei & Ren, Wen & Zheng, Bo-Chao & Han, Jinke, 2022. "Event-triggered adaptive sliding mode control of cyber-physical systems under false data injection attack," Applied Mathematics and Computation, Elsevier, vol. 433(C).
    4. Chen, Xiangyong & Park, Ju H. & Cao, Jinde & Qiu, Jianlong, 2017. "Sliding mode synchronization of multiple chaotic systems with uncertainties and disturbances," Applied Mathematics and Computation, Elsevier, vol. 308(C), pages 161-173.
    5. 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.
    6. Chu, Xiaoan & Li, Muguo, 2019. "Observer-based model following sliding mode tracking control of discrete-time linear networked systems with two-channel event-triggered schemes and quantizations," Applied Mathematics and Computation, Elsevier, vol. 355(C), pages 428-448.
    7. Gao, Meng & Zhang, Lihua & Qi, Wenhai & Cao, Jinde & Cheng, Jun & Kao, Yonggui & Wei, Yunliang & Yan, Xiaoyu, 2020. "SMC for semi-Markov jump T-S fuzzy systems with time delay," Applied Mathematics and Computation, Elsevier, vol. 374(C).

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