Data-based Optimal Control for Discrete-time Zero-sum Games of 2-D Systems Using Adaptive Critic Designs

作     者：WEI Qing-Lai ZHANG Hua-Guang CUI Li-Li 

作者机构：Institute of Automation Chinese Academy of Sciences Beijing 100190 The School of Information Science and Engineering Northeastern University Liaoning 110004 

出 版 物：《自动化学报》 

年 卷 期：2009年第35卷第6期

页      面：682-692页

学科分类：12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 08[工学] 

基　　金：国家863计划 国家自然科学基金 国家教育部长江学者与创新团队发展计划 

主　　题：Adaptive critic designs (ACD) optimal control zero-sum game 2-D system neural networks 

摘      要：In this paper, an iterative adaptive critic design (ACD) algorithm is proposed to solve a class of discrete-time twoperson zero-sum games for Roesser type 2-D system. The idea is to use adaptive critic technique to obtain the optimal control pair iteratively to make the performance index function reach the saddle point of the zero-sum games. The proposed iterative ACD algorithm can be implemented based on the input and state data without the system model. Stability analysis of the 2-D system is presented and the convergence property of the performance index function is also proved. Neural networks are used to approximate the performance index function and compute the optimal control policies, respectively, for facilitating the implementation of the iterative ACD algorithm. The optimal control scheme of the air drying process is given to illustrate the performance of the proposed method.