控制理论与应用2026，Vol.43Issue(5)：1034-1042,9.DOI:10.7641/CTA.2025.40256
锅炉汽轮机系统经验导向单评价Q-learning负荷控制
Experience-guided critic-only Q-learning load control for boiler-turbine system
摘要
Abstract
To address the challenges encountered in load control of boiler-turbine systems,such as the complexities in establishing precise mathematical models,asymmetric characteristics of valve constraints,and the limited methods for extracting operational experience data,this paper proposes an experience-guided critic-only Q-learning method for boiler-turbine systems adaptive load tracking control.A constraint transformation function is introduced to map asymmetrically constrained inputs to the median of the control range,effectively addressing the asymmetry issue,while reshaping the performance index function into a form without additional penalty terms.To reduce the online computational load,a lightweight critic-only network Q-learning algorithm is proposed to achieve fast learning of the improved performance index function.By updating strategies from previous episodes,an experience-guided relationship is established among multi-episode datasets online.Subsequently,a novel model for recurrent multi-episode training is formulated,aimed at op-timizing data mining efficiency and expediting algorithmic convergence.The effectiveness and superiority of the proposed control algorithm are verified by simulation on the 160 MW boiler-turbine system.关键词
锅炉-汽轮机系统/经验导向/单评价网络/Q-learning/负荷跟踪Key words
boiler-turbine system/experience-guided/critic-only network/Q-learning/load tracking引用本文复制引用
刘晓敏,余梦君,王浩宇,杨春雨,周林娜,周怀春..锅炉汽轮机系统经验导向单评价Q-learning负荷控制[J].控制理论与应用,2026,43(5):1034-1042,9.基金项目
国家自然科学基金项目(62073327,62273350,62303468,62303469),江苏省自然科学基金项目(BK20221112,BK20221116),中国博士后科学基金项目(2023M733757),江苏省卓越博士后计划项目(2022ZB530),山西省重点研究开发项目(202202100401002)资助.Supported by the National Natural Science Foundation of China(62073327,62273350,62303468,62303469),the National Natural Science Foun-dation of Jiangsu Province(BK20221112,BK20221116),the China Postdoctoral Science Foundation(2023M733757),the Excellent Post Doctorate Program of Jiangsu Province(2022ZB530)and the Key Research and Development projects in Shanxi Province(202202100401002). （62073327,62273350,62303468,62303469）
