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Robust Control of An Inverted Pendulum System Based on Policy Iteration in Reinforcement Learning
Version 1
: Received: 16 October 2023 / Approved: 17 October 2023 / Online: 17 October 2023 (13:04:30 CEST)
A peer-reviewed article of this Preprint also exists.
Ma, Y.; Xu, D.; Huang, J.; Li, Y. Robust Control of An Inverted Pendulum System Based on Policy Iteration in Reinforcement Learning. Appl. Sci. 2023, 13, 13181. Ma, Y.; Xu, D.; Huang, J.; Li, Y. Robust Control of An Inverted Pendulum System Based on Policy Iteration in Reinforcement Learning. Appl. Sci. 2023, 13, 13181.
Abstract
This paper is primarily focused on the robust control of an inverted pendulum system based
on the policy iteration in reinforcement learning. First, a mathematical model of the single inverted
pendulum system is established through a force analysis of the pendulum and trolley. Second,
based on the theory of robust optimal control, the robust control of the uncertain linear inverted
pendulum system is transformed into an optimal control problem with an appropriate performance
index. Moreover, for the uncertain linear and nonlinear systems, two reinforcement-learning control
algorithms are proposed using the policy iteration method. Finally, two numerical examples are
provided to validate the reinforcement learning algorithms for the robust control of the inverted
pendulum systems.
Keywords
robust control; optimal control; inverted pendulum system; reinforcement learning
Subject
Engineering, Control and Systems Engineering
Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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