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Observer-based model following sliding mode tracking control of discrete-time linear networked systems with two-channel event-triggered schemes and quantizations

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  • Chu, Xiaoan
  • Li, Muguo

Abstract

This paper addresses the problem of H∞ observer-based model following sliding mode tracking control for a class of linear discrete-time networked systems subject to event-triggered transmission schemes and quantizations occurring in both input and output channels. First, a dynamic event-triggered scheme and a static event-triggered scheme on sensor and controller sides are proposed, respectively, to reduce the number of unnecessary data transmission. Then, an observer is designed to estimate the system state. Considering the effects of quantization, networked conditions, external disturbance and event-triggered transmission schemes, the state error system and sliding mode dynamics are modeled as a new networked time-delay system. Based on this model and Lyapunov–Krasovskii functional method, sufficient conditions are derived to guarantee the resulting closed-loop system to be asymptotically stable with prescribed H∞ performance. And then, a co-design method is present to obtain the observer gain, triggering parameter and sliding mode parameter, simultaneously. Furthermore, a sliding mode controller for reaching motion is developed to ensure the reachability of the sliding surface. Finally, simulation examples are present to verify the effective of the proposed design method.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:apmaco:v:355:y:2019:i:c:p:428-448
    DOI: 10.1016/j.amc.2019.03.010
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    References listed on IDEAS

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    1. Chang, Xiao-Heng & Li, Zhi-Min & Xiong, Jun & Wang, Yi-Ming, 2017. "LMI approaches to input and output quantized feedback stabilization of linear systems," Applied Mathematics and Computation, Elsevier, vol. 315(C), pages 162-175.
    2. 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.
    3. Yueqiao Han & Yonggui Kao & Cunchen Gao & Baoping Jiang, 2017. "Robust sliding mode control for uncertain discrete singular systems with time-varying delays," International Journal of Systems Science, Taylor & Francis Journals, vol. 48(4), pages 818-827, March.
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    Cited by:

    1. Li, Baihua & Hu, Shaoyu & Zhong, Qishui & Shi, Kaibo & Zhong, Shouming, 2023. "Dynamic memory event-triggered proportional-integral-based H∞ load frequency control for multi-area wind power systems," Applied Mathematics and Computation, Elsevier, vol. 453(C).
    2. Li, Yankai & Chen, Mou & Li, Tao & Shi, Peng, 2020. "Anti-disturbance reference mode resilient dynamic output feedback control for turbofan systems," Applied Mathematics and Computation, Elsevier, vol. 378(C).
    3. Hu, Jun & Zhang, Panpan & Kao, Yonggui & Liu, Hongjian & Chen, Dongyan, 2019. "Sliding mode control for Markovian jump repeated scalar nonlinear systems with packet dropouts: The uncertain occurrence probabilities case," Applied Mathematics and Computation, Elsevier, vol. 362(C), pages 1-1.
    4. Shao, Xingling & Yue, Xiaohui & Li, Jie, 2021. "Event-triggered robust control for quadrotors with preassigned time performance constraints," Applied Mathematics and Computation, Elsevier, vol. 392(C).

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