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Event-Triggered iterative learning control for asynchronously switched systems

Author

Listed:
  • Qi, Yiwen
  • Qu, Ziyu
  • Yao, Zhaohui
  • Zhao, Xiujuan
  • Tang, Yiwen

Abstract

Iterative learning control (ILC) is an effective control strategy for complex systems that uses trial and error to obtain desired output trajectories. This paper focuses on the issue of event-triggered ILC for switched systems with asynchronous switching. An event-triggered ILC method is designed to reduce unnecessary controller updates during iterations. The main technical contribution is that the analysis and synthesis are performed in both time and iteration domains. First, in order to solve the asynchronous switching problem in the time direction and the update problem in the iteration direction, a Lyapunov function involving both directions is adopted. Second, to prove the convergence of tracking error and the system stability in both domains, a new prove method is proposed, in which the tracking error is summed over the entire time domain and the average dwell condition is summed over the entire iteration domain. Finally, the feasibility of theoretical result is verified by simulation.

Suggested Citation

  • Qi, Yiwen & Qu, Ziyu & Yao, Zhaohui & Zhao, Xiujuan & Tang, Yiwen, 2023. "Event-Triggered iterative learning control for asynchronously switched systems," Applied Mathematics and Computation, Elsevier, vol. 440(C).
    • Handle: RePEc:eee:apmaco:v:440:y:2023:i:c:s0096300322007305
    DOI: 10.1016/j.amc.2022.127662
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    References listed on IDEAS

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    1. Zhou, Xingyu & Tian, Yang & Wang, Haoping, 2022. "Neural network state observer-based robust adaptive fault-tolerant quantized iterative learning control for the rigid-flexible coupled robotic systems with unknown time delays," Applied Mathematics and Computation, Elsevier, vol. 430(C).
    2. Wang, Yingchun & Li, Haifeng & Qiu, Xiaojie & Xie, Xiangpeng, 2020. "Consensus tracking for nonlinear multi-agent systems with unknown disturbance by using model free adaptive iterative learning control," Applied Mathematics and Computation, Elsevier, vol. 365(C).
    3. Li, Weihua & Zhang, Huaguang & Wang, Wei & Cao, Zhengbao, 2022. "Fully distributed event-triggered time-varying formation control of multi-agent systems subject to mode-switching denial-of-service attacks," Applied Mathematics and Computation, Elsevier, vol. 414(C).
    4. Dong, Zeyu & Wang, Xin & Zhang, Xian, 2020. "A nonsingular M-matrix-based global exponential stability analysis of higher-order delayed discrete-time Cohen–Grossberg neural networks," Applied Mathematics and Computation, Elsevier, vol. 385(C).
    5. Deng, Yalin & Zhang, Huasheng & Dai, Yuzhen & Li, Yuanen, 2022. "Interval stability/stabilization for linear stochastic switched systems with time-varying delay," Applied Mathematics and Computation, Elsevier, vol. 428(C).
    6. 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).
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