Open AccessModel Predictive Control : A Reinforcement Learning-based Approach
Author(s) -
Xin Pan,
Xiaowei Chen,
Qingyu Zhang,
Nannan Li
Publication year - 2022
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/2203/1/012058
Subject(s) - reinforcement learning , model predictive control , computer science , adaptation (eye) , control (management) , reinforcement , artificial intelligence , stability (learning theory) , machine learning , engineering , psychology , structural engineering , neuroscience
This article proposes a method of model predictive control, which combine the excellent data-driven optimization ability of reinforcement learning and model predictive control to design the controller. Different from the off-line design of MPC, reinforcement learning is based on the adaptation of on-line data to achieve the purpose of control strategy optimization. The reinforcement learning-based model predictive control can improve the control performance effectively. And the numerical simulations are given to demonstrate the effectiveness of the proposed approach.