Affiliation:
1. Faculty of Information Technology Beijing University of Technology Beijing China
2. Beijing Key Laboratory of Computational Intelligence and Intelligent System Beijing University of Technology Beijing China
3. Beijing Institute of Artificial Intelligence Beijing University of Technology Beijing China
4. Beijing Laboratory of Smart Environmental Protection Beijing University of Technology Beijing China
Abstract
AbstractTo attenuate the effect of disturbances on control performance, a multi‐step adaptive critic control (MsACC) framework is developed to solve zero‐sum games for discrete‐time nonlinear systems. The MsACC algorithm utilizes multi‐step policy evaluation to obtain the solution of the Hamilton–Jacobi–Isaac equation, which is faster than that of the one‐step policy evaluation. The convergence rate of the MsACC algorithm is adjustable by varying the step size of the policy evaluation. In addition, the stability and convergence of the MsACC algorithm are proved under certain conditions. In order to realize the MsACC algorithm, three neural networks are established to approximate the control input, the disturbance input, and the cost function, respectively. Finally, the effectiveness of the MsACC algorithm is verified by two simulation examples, including a linear system and a nonlinear plant.
Funder
National Key Research and Development Program of China
National Natural Science Foundation of China
Beijing Natural Science Foundation
Subject
Electrical and Electronic Engineering,Industrial and Manufacturing Engineering,Mechanical Engineering,Aerospace Engineering,Biomedical Engineering,General Chemical Engineering,Control and Systems Engineering
Cited by
1 articles.
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