Reinforcement learning algorithm for adaptive intelligent control
145 viewsDOI:
https://doi.org/10.54939/1859-1043.j.mst.CAPITI.2024.62-68Keywords:
AI; Reinforcement learning; Intelligent control; Data-driven control; Adaptive control; PID.Abstract
Nowadays, with the development of science and technology, control objects are increasingly complex, have high nonlinearities and large uncertainties, making traditional classic control algorithms no longer effective. That leads to the construction of unknown structures and parameters and requires advanced control techniques. To solve control problems with unknown elements in the dynamic models of the control object, the intelligent adaptive control method based on reinforcement learning algorithm is capable of automatically adjusting the parameters of the controller, proposed by the authors in this article. The effectiveness and feasibility of the proposed method are verified through practical simulation. The obtained comparative simulation results confirm that the proposed controller is robust, adaptive, and has high control performance.
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