Regular Papers

International Journal of Control, Automation, and Systems 2024; 22(11): 3459-3471

https://doi.org/10.1007/s12555-024-0168-x

© The International Journal of Control, Automation, and Systems

An Estimator for Input Sent by ILC Controllers Through Multi-path Fading Channels

Lixun Huang*, Hui Chen, Lijun Sun, Bin Jiang, Yuanyuan Zhang, and Qiuwen Zhang

Zhengzhou University of Light Industry

Abstract

To ensure the convergence of objects controlled by the controller adopting iterative learning strategies through multi-path fading channels, this paper proposes an estimator for the controlled object to obtain the input sent by controllers. First, a controller adopting proportional learning strategies is considered, which shares input and output with the controlled object through the Rice fading channel. Secondly, utilizing the known information of both controllers and the Rice fading channel, the initial problem is converted into an estimation model. Finally, the estimator is created according to the orthogonality projection principle. Driving objects with the estimated input, significant improvements in tracking performance are achieved. Simulation results confirm the efficacy of the proposed estimator.

Keywords Convergence, estimator, iterative learning control, multi-path fading channels.

Article

Regular Papers

International Journal of Control, Automation, and Systems 2024; 22(11): 3459-3471

Published online November 1, 2024 https://doi.org/10.1007/s12555-024-0168-x

Copyright © The International Journal of Control, Automation, and Systems.

An Estimator for Input Sent by ILC Controllers Through Multi-path Fading Channels

Lixun Huang*, Hui Chen, Lijun Sun, Bin Jiang, Yuanyuan Zhang, and Qiuwen Zhang

Zhengzhou University of Light Industry

Abstract

To ensure the convergence of objects controlled by the controller adopting iterative learning strategies through multi-path fading channels, this paper proposes an estimator for the controlled object to obtain the input sent by controllers. First, a controller adopting proportional learning strategies is considered, which shares input and output with the controlled object through the Rice fading channel. Secondly, utilizing the known information of both controllers and the Rice fading channel, the initial problem is converted into an estimation model. Finally, the estimator is created according to the orthogonality projection principle. Driving objects with the estimated input, significant improvements in tracking performance are achieved. Simulation results confirm the efficacy of the proposed estimator.

Keywords: Convergence, estimator, iterative learning control, multi-path fading channels.

IJCAS
March 2025

Vol. 23, No. 3, pp. 683~972

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