Design and application of adaptive PID controller based on asynchronous advantage actor–critic learning method
Qifeng Sun, Chengze Du, Youxiang Duan, Hui Ren, Hongqiang Li · Wireless Networks · 2019
Abstract To address the problems of the slow convergence and inefficiency in the existing adaptive PID controllers, we propose a new adaptive PID controller using the asynchronous advantage actor–critic (A3C) algorithm. Firstly, the controller can train the multiple agents of the actor–critic structures in parallel exploiting the multi-thread asynchronous learning characteristics of the A3C structure. Secondly, in order to achieve the best control effect, each agent uses a multilayer neural network to approach the strategy function and value function to search the best parameter-tuning strategy in continuous action space. The simulation results indicate that our proposed controller can achieve the fast convergence and strong adaptability compared with conventional controllers.