Reinforcement learning-based optimal control of uncertain nonlinear systems

Authors

Miguel Garcia, The University of Texas Rio Grande Valley
Wenjie Dong, The University of Texas Rio Grande Valley

Document Type

Article

Publication Date

12-2024

Abstract

This paper considers the optimal control of a second-order nonlinear system with unknown dynamics. A new reinforcement learning based approach is proposed with the aid of direct adaptive control. By the new approach actor-critic reinforcement learning algorithms are proposed with three neural network approximation. Simulation results are presented to show the effectiveness of the proposed algorithms.

Comments

Original published version available at https://doi.org/10.1080/00207179.2024.2305727

Recommended Citation

Garcia, Miguel, and Wenjie Dong. "Reinforcement learning-based optimal control of uncertain nonlinear systems." International Journal of Control 97, no. 12 (2024): 2839-2850. https://doi.org/10.1080/00207179.2024.2305727

Publication Title

International Journal of Control

DOI

10.1080/00207179.2024.2305727