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Relaxed stabilization synthesis of discrete-time nonlinear systems with uplink data loss based on a novel online evaluation mechanism

Author

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  • Xie, Xiangpeng
  • Shen, Xicheng
  • Peng, Chen

Abstract

The problem of promoting the adaptability to uplink data loss for nonlinear plant is addressed via developing the fuzzy gain-scheduling stabilization law based on a novel online evaluation mechanism. Different from those previous methods, the proposed online evaluation mechanism is dependent not only the current-time but also the past-time normalized fuzzy weighting functions, and thus much more information can be absorbed and utilized in the process of stabilization synthesis by introducing extra free matrices than before. More importantly, an additional constraint is for the first time proposed for updating the plant status instantly so that critical replacement operations can be implemented for reducing the conservativeness of the designing conditions. Therefore, the adaptability to uplink data loss is improved evidently and thus the worse communication quality of uplink channel is bearable in this study. Finally, the advantages relative to those reported ones are tested and validated through benchmark numerical comparisons.

Suggested Citation

  • Xie, Xiangpeng & Shen, Xicheng & Peng, Chen, 2022. "Relaxed stabilization synthesis of discrete-time nonlinear systems with uplink data loss based on a novel online evaluation mechanism," Applied Mathematics and Computation, Elsevier, vol. 421(C).
    • Handle: RePEc:eee:apmaco:v:421:y:2022:i:c:s0096300322000352
    DOI: 10.1016/j.amc.2022.126949
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    References listed on IDEAS

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    1. Lee, Tae H. & Park, Myeong Jin & Park, Ju H., 2021. "An improved stability criterion of neural networks with time-varying delays in the form of quadratic function using novel geometry-based conditions," Applied Mathematics and Computation, Elsevier, vol. 404(C).
    2. 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).
    3. Cui, Lili & Zhang, Yong & Wang, Xiaowei & Xie, Xiangpeng, 2021. "Event-triggered distributed self-learning robust tracking control for uncertain nonlinear interconnected systems," Applied Mathematics and Computation, Elsevier, vol. 395(C).
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