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Adaptive Critic Learning-Based Robust Control of Systems with Uncertain Dynamics.

Authors :
Zhao, Jun
Zeng, Qingliang
Guo, Bin
Source :
Computational Intelligence & Neuroscience. 11/16/2021, p1-8. 8p.
Publication Year :
2021

Abstract

Model uncertainties are usually unavoidable in the control systems, which are caused by imperfect system modeling, disturbances, and nonsmooth dynamics. This paper presents a novel method to address the robust control problem for uncertain systems. The original robust control problem of the uncertain system is first transformed into an optimal control of nominal system via selecting the appropriate cost function. Then, we develop an adaptive critic leaning algorithm to learn online the optimal control solution, where only the critic neural network (NN) is used, and the actor NN widely used in the existing methods is removed. Finally, the feasibility analysis of the control algorithm is given in the paper. Simulation results are given to show the availability of the presented control method. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
16875265
Database :
Academic Search Index
Journal :
Computational Intelligence & Neuroscience
Publication Type :
Academic Journal
Accession number :
153608970
Full Text :
https://doi.org/10.1155/2021/2952115