Dynamic Decentralized Event-Triggered Tracking Control of Continuous Stirred Tank Reactor Systems

作     者：Yang, Xiong Meng, Jianling Wei, Qinglai 

作者机构：Tianjin University Tianjin Key Laboratory of Intelligent Unmanned Swarm Technology and System School of Electrical and Information Engineering Tianjin 300072 China Chinese Academy of Sciences State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Beijing 100190 China University of Chinese Academy of Sciences School of Artificial Intelligence Beijing 100049 China 

出 版 物：《IEEE Transactions on Automation Science and Engineering》 (IEEE Trans. Autom. Sci. Eng.)

年 卷 期：2025年第22卷

页      面：16632-16643页

学科分类：0808[工学-电气工程] 0809[工学-电子科学与技术（可授工学、理学学位）] 08[工学] 0802[工学-机械工程] 0811[工学-控制科学与工程] 

基　　金：National Natural Science Foundation of China, NNSFC, (62373267, 61973228) National Natural Science Foundation of China, NNSFC 

主　　题：Adaptive dynamic programming (ADP) continuous stirred tank reactor (CSTR) decentralized tracking control event-triggered control optimal control 

摘      要：We develop a dynamic decentralized event-triggered tracking control strategy for cascade interconnected continuous stirred tank reactor (CSTR) systems subject to asymmetric input limits. Initially, we construct auxiliary augmented subsystems related to the cascade interconnected CSTR systems. Then, by introducing modified nonquadratic cost functions for the auxiliary augmented subsystems, we convert the decentralized constrained tracking control problem into an array of unconstrained optimal regulation problems. After that, with the construction of dynamic event-triggering mechanisms, we propose the event-triggered Hamilton-Jacobi-Bellman equations (ET-HJBEs) associated with the transformed optimal regulation problems. To approximately solve the ET-HJBEs, we design critic neural networks (CNNs) in the adaptive dynamic programming framework with the CNNs’ weights being updated through the gradient descent method. Furthermore, we use Lyapunov method to prove that the CNNs’ weight estimation errors and the tracking error are stable in the sense of uniform ultimate boundedness. Finally, simulation results of the three-reactor cascade interconnected CSTR systems are provided to validate the present dynamic decentralized event-triggered tracking control scheme. © 2004-2012 IEEE.