Regulation with Guaranteed Convergence Rate for Continuous-Time Systems with Completely Unknown Dynamics in the Presence of Disturbance

Rahdarian, Ali and Zadeh, Danial Sadrian and Shamaghdari, Saeed and Moshiri, Behzad and Montazeri, Allahyar (2022) Regulation with Guaranteed Convergence Rate for Continuous-Time Systems with Completely Unknown Dynamics in the Presence of Disturbance. IEEE Access, 10. pp. 122376-122386. ISSN 2169-3536

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Abstract

This paper presents the design of a novel H ∞ -based control framework for state regulation of continuous-time linear systems with completely unknown dynamics. The proposed method solves the regulation problem with the desired convergence rate and simultaneously seeks to attenuate the adverse effect of disturbance on the system. The H ∞ regulation problem assumes a cost function that considers regulation with a guaranteed rate of convergence as well as disturbance attenuation. The problem is then turned into a two-player zero-sum game optimization problem that can be solved by solving the associated algebraic Riccati equation (ARE), which provides a model-based solution. To solve this problem in a model-free way, a novel integral reinforcement learning (IRL) algorithm is designed to learn the solution online without requiring any prior knowledge of the system dynamics. It is shown that the model-free method (i.e., IRL-based method) provides the same solution as the model-based method (i.e., ARE). The effectiveness of the proposed method is ascertained through simulation examples; it is shown that the proposed method effectively addresses the problem for both stable and unstable systems.

Item Type:
Journal Article
Journal or Publication Title:
IEEE Access
Uncontrolled Keywords:
/dk/atira/pure/subjectarea/asjc/2200/2200
Subjects:
?? general engineeringgeneral materials sciencegeneral computer scienceelectrical and electronic engineeringgeneral engineeringgeneral computer sciencegeneral materials scienceengineering(all)computer science(all)materials science(all) ??
ID Code:
176809
Deposited By:
Deposited On:
11 Oct 2022 09:15
Refereed?:
Yes
Published?:
Published
Last Modified:
16 Jul 2024 11:55