集成技术2026，Vol.15Issue(5)：64-82,19.DOI:10.12146/j.issn.2095-3135.20260518001
具备安全机制的高效强化学习工业过程控制方法
Efficient Reinforcement Learning with Safety Mechanism for Industrial Process Control
摘要
Abstract
Conventional reinforcement learning methods are prone to triggering dangerous states due to random exploration in the early training stage,which limits their application to industrial process control characterized by strong coupling,strong nonlinearity,and strict safety constraints.Safe reinforcement learning can reduce operational risks during reinforcement learning training and deployment to some extent by constraining policy exploration,correcting high-risk actions,or incorporating safety priors.This paper proposes a multi-agent continuous dynamic strategy planning method with a safety mechanism for the multivariable continuous control problem of an ethylene glycol distillation column.In this method,the reboiler steam flow rate,overhead reflux flow rate,bottom product draw flow rate,side draw flow rate,and post-cooling side draw temperature are modeled as actions of multiple cooperative agents.A safety mechanism based on the column bottom level and ethylene glycol purity is introduced.Both the original policy actions and the safety-corrected executed actions are stored in the replay buffer.Under the centralized training with decentralized execution framework,relative entropy regularization and safety intervention information are used to constrain subsequent policy updates.Simulation results on the ethylene glycol distillation column show that,after 40 days of training,the proposed method increases production rate by 5.7%and average net profit by 48.68%compared with human operation,while maintaining product purity within the quality constraint.The proposed method improves economic benefits and learning stability in chemical process control,while ensuring operational safety during early-stage random exploration.关键词
强化学习/多智能体控制/乙二醇精馏塔/动态策略规划/安全机制Key words
reinforcement learning/multi-agent control/ethylene glycol distillation column/dynamic policy programming/safety mechanism分类
信息技术与安全科学引用本文复制引用
刘光玉,黄文俊,张惠泽,崔允端,喻学锋..具备安全机制的高效强化学习工业过程控制方法[J].集成技术,2026,15(5):64-82,19.基金项目
广东省重点研发计划项目(2025B0101130005) This work is supported by Guangdong Science and Technology Program(2025B0101130005) （2025B0101130005）
