@inproceedings{d258b172176b4d469408c9310a8e8a10,
title = "Adaptive Repetitive Learning Control for Dual-Motor Driving Servo Systems",
abstract = "In this paper, an adaptive repetitive learning control strategy is proposed for dual-motor driving servo systems with uncertainties. First, a mean relative coupling synchronization controller is designed that achieves fast synchronization and avoids the coupling problem. Next, a fully saturated repetitive learning law is utilized for designing the unknown desired control input such that the periodic uncertainty is compensated. The neural network-based robust control input with is also proposed to compensate the non-periodic uncertainty. Finally, the results are verified with a simulation of the two-motor drive system.",
keywords = "Dual-motor driving servo systems, Periodic uncertainty, Repetitive learning, Synchronization",
author = "Shuangyi Hu and Qiang Chen and Xuemei Ren",
note = "Publisher Copyright: {\textcopyright} 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.; 19th Chinese Intelligent Systems Conference, CISC 2023 ; Conference date: 14-10-2023 Through 15-10-2023",
year = "2023",
doi = "10.1007/978-981-99-6886-2_49",
language = "English",
isbn = "9789819968855",
series = "Lecture Notes in Electrical Engineering",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "567--578",
editor = "Yingmin Jia and Weicun Zhang and Yongling Fu and Jiqiang Wang",
booktitle = "Proceedings of 2023 Chinese Intelligent Systems Conference - Volume III",
address = "Germany",
}