A New Integral Critic Learning for Optimal Tracking Control with Applications to Boiler-Turbine Systems

doi:10.1002/oca.2792

CORC > 自动化研究所 > 中国科学院自动化研究所 > 复杂系统管理与控制国家重点实验室 > 智能化团队

	A New Integral Critic Learning for Optimal Tracking Control with Applications to Boiler-Turbine Systems
	Wei, Qinglai 3; Liu, Yujia 3; Lu, Jingwei 3; Ling, Jun 1; Luan, Zhenhua 2; Chen, Mingliang 2
刊名	OPTIMAL CONTROL APPLICATIONS & METHODS
	2021-10-12
页码	16
关键词	adaptive dynamic programming boiler-turbine system integral reinforcement learning neural network policy iteration
ISSN号	0143-2087
DOI	10.1002/oca.2792
通讯作者	Wei, Qinglai(qinglai.wei@ia.ac.cn)
英文摘要	Optimal control theory and reinforcement learning are gradually being used in the field of industrial control. In this article, a new optimal tracking control scheme for 160 MW boiler-turbine systems is proposed based on an online policy iteration integral reinforcement learning (IRL) method. Firstly, a self-learning state tracking control with a cost function is developed to deal with the optimal tracking control problems for the boiler-turbine nonlinear system. Then with a modified cost function, a policy iteration-based IRL method is introduced to obtain the optimal control law. Finally, the monotonicity and the convergence of the cost function is analyzed and the detailed implementation of the policy iteration-based IRL method is provided via neural networks. The simulation results show that the control of the boiler-turbine system can converge in a short time by using this online iterative method. Through a theoretical simulation case, it can be concluded that the proposed method is more advanced compared with the MPC method.
资助项目	National Key Research and Development Program of China[2018YFB1702300] ; National Key Research and Development Program of China[2018AAA0101502] ; National Natural Science Foundation of China[62073321] ; National Natural Science Foundation of China[61873300]
WOS关键词	NONLINEAR-SYSTEMS ; PARALLEL CONTROL ; DRUM ; UNIT
WOS研究方向	Automation & Control Systems ; Operations Research & Management Science ; Mathematics
语种	英语
出版者	WILEY
WOS记录号	WOS:000706550400001
资助机构	National Key Research and Development Program of China ; National Natural Science Foundation of China
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/46182]
专题	自动化研究所_复杂系统管理与控制国家重点实验室_智能化团队
通讯作者	Wei, Qinglai
作者单位	1.Shanghai Jiao Tong Univ, Dept Automat, Shanghai, Peoples R China 2.China Nucl Power Engn CO LTD, State Key Lab Nucl Power Safety Monitoring Techno, Shenzhen, Guangdong, Peoples R China 3.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing, Peoples R China
推荐引用方式 GB/T 7714	Wei, Qinglai,Liu, Yujia,Lu, Jingwei,et al. A New Integral Critic Learning for Optimal Tracking Control with Applications to Boiler-Turbine Systems[J]. OPTIMAL CONTROL APPLICATIONS & METHODS,2021:16.
APA	Wei, Qinglai,Liu, Yujia,Lu, Jingwei,Ling, Jun,Luan, Zhenhua,&Chen, Mingliang.(2021).A New Integral Critic Learning for Optimal Tracking Control with Applications to Boiler-Turbine Systems.OPTIMAL CONTROL APPLICATIONS & METHODS,16.
MLA	Wei, Qinglai,et al."A New Integral Critic Learning for Optimal Tracking Control with Applications to Boiler-Turbine Systems".OPTIMAL CONTROL APPLICATIONS & METHODS (2021):16.