Robust Control of An Inverted Pendulum System Based on Policy Iteration in Reinforcement Learning

Autor: Yan Ma, Dengguo Xu, Jiashun Huang, Yahui Li
Jazyk: angličtina
Rok vydání: 2023
Předmět:
Zdroj: Applied Sciences, Vol 13, Iss 24, p 13181 (2023)
Druh dokumentu: article
ISSN: 2076-3417
DOI: 10.3390/app132413181
Popis: This paper is primarily focused on the robust control of an inverted pendulum system based on 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.
Databáze: Directory of Open Access Journals