自动化学报2009，Vol.35Issue(6)：682-692,11.DOI:10.3724/SP.J.1004.2009.00682
基于数据自适应证券的离散2-D系统零和博弈最优控制
Data-based Optimal Control for Discrete-time Zero-sum Games of 2-D Systems Using Adaptive Critic Designs
摘要
Abstract
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.关键词
Adaptive critic designs (ACD), optimal control, zero-sum game, 2-D system, neural networksKey words
Adaptive critic designs (ACD), optimal control, zero-sum game, 2-D system, neural networks分类
信息技术与安全科学引用本文复制引用
魏庆来,张化光,崔黎黎..基于数据自适应证券的离散2-D系统零和博弈最优控制[J].自动化学报,2009,35(6):682-692,11.基金项目
Supported by National High Technology Research and Development Program of China (863 Program) (2006AA04Z183), National Natural Science Foundation of China (60621001, 60534010, 60572070, 60774048, 60728307), Program for Changjiang Scholars and Innovative Research Groups of China (60728307,4031002) （863 Program）
