Robust optimal control for a class of nonlinear systems with unknown disturbances based on disturbance observer and policy iteration

A robust optimal control method for a class of nonlinear systems with unknown disturbances is addressed in this paper. In this framework, adaptive dynamic programming (ADP) is presented to obtain the optimal control. On-policy learning allows the performance index function and the optimal control to...

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Published in:	Neurocomputing (Amsterdam) Vol. 390; pp. 185 - 195
Main Authors:	Song, Ruizhuo, Lewis, Frank L.
Format:	Journal Article
Language:	English
Published:	Elsevier B.V 21.05.2020
Subjects:	Adaptive critic designs Adaptive dynamic programming Approximate dynamic programming Disturbance On-policy Optimal control Approximate dynamic programming Adaptive dynamic programming On-policy Optimal control Adaptive critic designs Disturbance
ISSN:	0925-2312, 1872-8286
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Abstract	A robust optimal control method for a class of nonlinear systems with unknown disturbances is addressed in this paper. In this framework, adaptive dynamic programming (ADP) is presented to obtain the optimal control. On-policy learning allows the performance index function and the optimal control to be obtained iteratively. It is shown that the iterative performance index function is non-increasing. A nonlinear disturbance observer is designed to estimate external disturbances. The compensation control is used to compensate for the influence of the disturbances. It is proven that the disturbance observer error is exponentially stable, under some conditions. The properties of the nonlinear system with unknown disturbance steered by the robust optimal control input are also proven. Simulation results demonstrate the performance of the proposed robust optimal control scheme for the nonlinear system with unknown disturbance.
AbstractList	A robust optimal control method for a class of nonlinear systems with unknown disturbances is addressed in this paper. In this framework, adaptive dynamic programming (ADP) is presented to obtain the optimal control. On-policy learning allows the performance index function and the optimal control to be obtained iteratively. It is shown that the iterative performance index function is non-increasing. A nonlinear disturbance observer is designed to estimate external disturbances. The compensation control is used to compensate for the influence of the disturbances. It is proven that the disturbance observer error is exponentially stable, under some conditions. The properties of the nonlinear system with unknown disturbance steered by the robust optimal control input are also proven. Simulation results demonstrate the performance of the proposed robust optimal control scheme for the nonlinear system with unknown disturbance.
Author	Lewis, Frank L. Song, Ruizhuo
Author_xml	– sequence: 1 givenname: Ruizhuo orcidid: 0000-0002-6693-2738 surname: Song fullname: Song, Ruizhuo email: ruizhuosong@ustb.edu.cn organization: School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing 100083, China – sequence: 2 givenname: Frank L. surname: Lewis fullname: Lewis, Frank L. email: lewis@uta.edu organization: UTA Research Institute, University of Texas at Arlington, Fort Worth, TX 76118, USA
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Snippet	A robust optimal control method for a class of nonlinear systems with unknown disturbances is addressed in this paper. In this framework, adaptive dynamic...
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SubjectTerms	Adaptive critic designs Adaptive dynamic programming Approximate dynamic programming Disturbance On-policy Optimal control
Title	Robust optimal control for a class of nonlinear systems with unknown disturbances based on disturbance observer and policy iteration
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