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State Estimators for Plants Implementing ILC Strategies through Delay Links

Author

Listed:
  • Lina Si

    (School of Computer Science and Technology, Zhengzhou University of Light Industry, Zhengzhou 450066, China)

  • Xinyang Guo

    (School of Electrical and Information Engineering, Henan University of Engineering, Zhengzhou 451191, China)

  • Lixun Huang

    (School of Electronics and Information, Zhengzhou University of Light Industry, Zhengzhou 450066, China)

  • Qiuwen Zhang

    (School of Computer Science and Technology, Zhengzhou University of Light Industry, Zhengzhou 450066, China)

Abstract

Random delays in the communication links affect the precise tracking of the expected trajectory by a plant controlled by the iterative learning control (ILC) strategy. To tackle the link impact, this paper proposes a state estimator to derive accurate plant outputs that are necessary for controller learning. First, a data pre-processing method is designed to ensure that both the controller and actuator ends receive only one piece of data at any given moment. Subsequently, the data pre-processing method and the system information are used according to the theory of orthogonality to construct the state estimator. The simulation examples demonstrate that the developed estimators aid in the precise tracking of the desired trajectory by the plant implementing ILC strategies through delay links.

Suggested Citation

  • Lina Si & Xinyang Guo & Lixun Huang & Qiuwen Zhang, 2024. "State Estimators for Plants Implementing ILC Strategies through Delay Links," Mathematics, MDPI, vol. 12(18), pages 1-18, September.
    • Handle: RePEc:gam:jmathe:v:12:y:2024:i:18:p:2834-:d:1476987
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    References listed on IDEAS

    as
    1. Fu, Xingjian & Peng, Jianshuai, 2023. "Iterative learning control for UAVs formation based on point-to-point trajectory update tracking," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 209(C), pages 1-15.
    2. Chen, Dongjie & Xu, Ying & Lu, Tiantian & Li, Guojun, 2024. "Multi-phase iterative learning control for high-order systems with arbitrary initial shifts," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 216(C), pages 231-245.
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