首页> 中文会议>第33期双清论坛——基于数据的控制、决策、调度与故障诊断 >基于数据自适应证券的离散2-D系统零和博弈最优控制

基于数据自适应证券的离散2-D系统零和博弈最优控制

摘要

In this paper, an iterative adaptive critic design (ACD) algorithm is proposed to solve a class of discrete-time two-person 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 sir drying process isgiven to illustrate the performance of the proposed method.

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