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基于强化学习的舞台多轴同步系统预测维护策略研究

李炜 王洁莹 毛海杰

湖南大学学报(自然科学版)2024,Vol.51Issue(12):176-185,10.
湖南大学学报(自然科学版)2024,Vol.51Issue(12):176-185,10.DOI:10.16339/j.cnki.hdxbzkb.2024294

基于强化学习的舞台多轴同步系统预测维护策略研究

Research on Predictive Maintenance Strategy for Stage Multi-axis Synchronous System Based on Reinforcement Learning

李炜 1王洁莹 2毛海杰1

作者信息

  • 1. 兰州理工大学 电气工程与信息工程学院,甘肃 兰州 730050||甘肃省工业过程先进控制重点实验室,甘肃 兰州 730050
  • 2. 兰州理工大学 电气工程与信息工程学院,甘肃 兰州 730050
  • 折叠

摘要

Abstract

Aiming at the problem that the performance of the stage multi-axis synchronous system cannot meet the time limit of the control task due to the degradation of the actuators,and the existing maintenance strategy is difficult to reach the optimization,this paper proposes a reinforcement learning-based predictive maintenance strategy for the stage multi-axis synchronous system.Firstly,reinforcement learning is introduced in a cascaded manner,and constructing a control architecture with capabilities for lifespan prediction and autonomous maintenance,which operates with different sampling rates.Secondly,focusing on the intervening maintenance strategy and the influence of multi-source uncertainty on the actuator degradation process,based on the algorithms of Kalman filtering,Expectation-Maximum,and Rauch-Tung-Striebel smoothing,by the real-time perception and estimation of actuator degradation state,and a daptive update of degradation model,the prediction accuracy of the remaining life of the multi-axis synchronous system is ensured.Combined with the real-time perception,deviation of remaining life prediction,and the actuator degradation state,the objective function of a Q-learning algorithm is constructed.The optimal adjustment of maintenance control is carried out through trials and errors to obtain the maximum life extension reward and realize intelligent optimization maintenance of the stage multi-axis synchronous system.Finally,the effectiveness of the proposed method is verified by simulation experiments of the stage multi-axis synchronous control system,improving the system maintenance efficiency.

关键词

舞台多轴同步/执行器退化/剩余寿命预测/强化学习/预测维护

Key words

stage multi-axis synchronous system/actuator degradation/residual life prediction/reinforcement learning/predictive maintenance

分类

信息技术与安全科学

引用本文复制引用

李炜,王洁莹,毛海杰..基于强化学习的舞台多轴同步系统预测维护策略研究[J].湖南大学学报(自然科学版),2024,51(12):176-185,10.

基金项目

国家自然科学基金资助项目(62063017),National Natural Science Foundation of China(62063017) (62063017)

湖南大学学报(自然科学版)

OA北大核心CSTPCD

1674-2974

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