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基于强化学习自适应自耦PID的可控永磁悬浮系统控制研究

胡坤 孙亚伟 蒋浩 陈卓 许刚

中南大学学报(自然科学版)2026,Vol.57Issue(7):3043-3059,17.
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中南大学学报(自然科学版)2026,Vol.57Issue(7):3043-3059,17.DOI:10.11817/j.issn.1672-7207.2026.07.014

基于强化学习自适应自耦PID的可控永磁悬浮系统控制研究

Research on adaptive self-coupling PID control for controllable permanent magnet levitation systems based on reinforcement learning

胡坤 1孙亚伟 2蒋浩 2陈卓 2许刚2

作者信息

  • 1. 安徽理工大学机电工程学院,安徽 淮南,232001||煤炭无人化开采数智技术全国重点实验室,安徽 淮南,232001
  • 2. 安徽理工大学机电工程学院,安徽 淮南,232001
  • 折叠

摘要

Abstract

The controllable permanent magnet levitation belt conveyor is a novel type of magnetic levitation belt conveyor that uses controllable permanent magnet levitation rollers as its supporting structure.Aiming at the nonlinearity and susceptibility to interference of its controllable permanent magnet levitation system,a control method integrating the reinforcement-learning deep deterministic policy gradient(DDPG)algorithm and self-coupling PID(SC-PID)was proposed.The DDPG algorithm serves as the upper-layer control strategy,which learns the nonlinear characteristics of the controllable permanent magnet levitation system to adaptively adjust the speed factor parameters of the lower-layer SC-PID control.Moreover,to address the low exploration efficiency in the early training phase of the DDPG algorithm,a double replay buffer mechanism was introduced to enhance the algorithm's training efficiency in the initial stage.The simulation and experimental results show that compared with the PID and SC-PID control methods,the proposed control method can quickly adjust control parameters according to the system tracking error,demonstrating excellent tracking and anti-interference performance.Under external load impact disturbances,the change in the system's levitation gap is 0.29 mm,which is a reduction of 32.5%and 19.4%compared to the PID and SC-PID control methods,respectively.This improvement in the dynamic performance of the controllable permanent magnet levitation system proves the superiority brought about by the intelligent adjustment of controller parameters.

关键词

可控永磁悬浮系统/DDPG算法/自耦PID/双经验回放池

Key words

controllable permanent magnet levitation system/deep deterministic policy gradient(DDPG)algorithm/self-coupling PID/double replay buffer

分类

机械制造

引用本文复制引用

胡坤,孙亚伟,蒋浩,陈卓,许刚..基于强化学习自适应自耦PID的可控永磁悬浮系统控制研究[J].中南大学学报(自然科学版),2026,57(7):3043-3059,17.

基金项目

国家自然科学基金资助项目(52274153) (52274153)

安徽省高校学科拔尖人才学术资助项目(gxbjZD2022015)(Project(52274153)supported by the National Natural Science Foundation of China (gxbjZD2022015)

Project(gxbjZD2022015)supported by the Top Talent Academic Support Program for Discipline Leaders in Anhui Province) (gxbjZD2022015)

中南大学学报(自然科学版)

1672-7207

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