IDEAS home Printed from https://ideas.repec.org/a/eee/apmaco/v440y2023ics0096300322007305.html
   My bibliography  Save this article

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
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0096300322007305
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.amc.2022.127662?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. 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).
    2. 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).
    3. 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).
    4. 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).
    5. 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).
    6. 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).
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Zhu, Lin & Che, Wei-Wei & Jin, Xiao-Zheng, 2022. "Dynamic event-triggered tracking control for model-free networked control systems," Applied Mathematics and Computation, Elsevier, vol. 431(C).
    2. Zheng, Wei & Zhang, Zhiming & Lam, Hak-Keung & Sun, Fuchun & Wen, Shuhuan, 2023. "LMIs-based exponential stabilization for interval delay systems via congruence transformation: Application in chaotic Lorenz system," Chaos, Solitons & Fractals, Elsevier, vol. 176(C).
    3. Hua, Wentao & Wang, Yantao & Liu, Chunyan, 2024. "New method for global exponential synchronization of multi-link memristive neural networks with three kinds of time-varying delays," Applied Mathematics and Computation, Elsevier, vol. 471(C).
    4. Ding, Hongfei & Wang, Yudong & Shen, Hao, 2024. "A reinforcement learning integral sliding mode control scheme against lumped disturbances in hot strip rolling," Applied Mathematics and Computation, Elsevier, vol. 465(C).
    5. Meng, Xianhe & Zhang, Xian & Wang, Yantao, 2023. "Bounded real lemmas and exponential H∞ control for memristor-based neural networks with unbounded time-varying delays," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 210(C), pages 66-81.
    6. Chen, Yonghui & Zhang, Xian & Xue, Yu, 2022. "Global exponential synchronization of high-order quaternion Hopfield neural networks with unbounded distributed delays and time-varying discrete delays," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 193(C), pages 173-189.
    7. Yao, Dajie & Dou, Chunxia & Xie, Xiangpeng & Hu, Songlin, 2022. "Containment control of non-affine multi-agent systems based on given precision," Applied Mathematics and Computation, Elsevier, vol. 412(C).
    8. Li, Yuanen & Zhang, Huasheng & Zhang, Tingting & Geng, Han, 2023. "Interval stability/stabilization and H∞ feedback control for linear impulsive stochastic systems," Applied Mathematics and Computation, Elsevier, vol. 437(C).
    9. Solat, Amirhossein & Gharehpetian, G.B. & Naderi, Mehdi Salay & Anvari-Moghaddam, Amjad, 2024. "On the control of microgrids against cyber-attacks: A review of methods and applications," Applied Energy, Elsevier, vol. 353(PA).
    10. Zhang, Weijian & Du, Haibo & Chu, Zhaobi, 2022. "Robust discrete-time non-smooth consensus protocol for multi-agent systems via super-twisting algorithm," Applied Mathematics and Computation, Elsevier, vol. 413(C).
    11. Zhao, Huarong & Peng, Li & Yu, Hongnian, 2022. "Quantized model-free adaptive iterative learning bipartite consensus tracking for unknown nonlinear multi-agent systems," Applied Mathematics and Computation, Elsevier, vol. 412(C).
    12. Xie, Lifei & Cheng, Jun & Wang, Hailing & Wang, Jiange & Hu, Mengjie & Zhou, Zhidong, 2022. "Memory-based event-triggered asynchronous control for semi-Markov switching systems," Applied Mathematics and Computation, Elsevier, vol. 415(C).
    13. Chen, Wu-Hua & Sun, Hao & Lu, Xiaomei, 2024. "A variable gain impulsive observer for perturbed Lipschitz nonlinear systems with delayed discrete measurements," Applied Mathematics and Computation, Elsevier, vol. 473(C).
    14. Wang, Chen & Qi, Yiwen & Tang, Yiwen & Li, Xin & Ji, Ming, 2024. "Robust control with protected feedback information for switched systems under injection attacks," Applied Mathematics and Computation, Elsevier, vol. 475(C).
    15. Yang, Ni & Gao, Ruiyi & Su, Huan, 2022. "Stability of multi-links complex-valued impulsive stochastic systems with Markovian switching and multiple delays," Chaos, Solitons & Fractals, Elsevier, vol. 164(C).
    16. Zhang, Zhongjie & Yu, Tingting & Zhang, Xian, 2022. "Algebra criteria for global exponential stability of multiple time-varying delay Cohen–Grossberg neural networks," Applied Mathematics and Computation, Elsevier, vol. 435(C).
    17. Sun, Yuting & Hu, Cheng & Yu, Juan & Shi, Tingting, 2023. "Synchronization of fractional-order reaction-diffusion neural networks via mixed boundary control," Applied Mathematics and Computation, Elsevier, vol. 450(C).
    18. Wang, Junlan & Wang, Xin & Wang, Yantao & Zhang, Xian, 2021. "Non-reduced order method to global h-stability criteria for proportional delay high-order inertial neural networks," Applied Mathematics and Computation, Elsevier, vol. 407(C).
    19. Yu, Peilin & Deng, Feiqi, 2022. "Stabilization analysis of Markovian asynchronous switched systems with input delay and Lévy noise," Applied Mathematics and Computation, Elsevier, vol. 422(C).
    20. Zhang, Jianan & Ma, Yuechao, 2023. "Adaptive fault-tolerant double asynchronous control for switched semi-Markov jump systems via improved memory sampled-data technique," Chaos, Solitons & Fractals, Elsevier, vol. 174(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:apmaco:v:440:y:2023:i:c:s0096300322007305. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/applied-mathematics-and-computation .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.