Abstract
To address the problems of the slow convergence and inefficiency in the existing adaptive PID controllers, we proposed a new adaptive PID controller using the Asynchronous Advantage Actor-Critic (A3C) algorithm. Firstly, the controller can parallel train the multiple agents of the Actor-Critic (AC) structures 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 indicated that our proposed controller can achieve the fast convergence and strong adaptability compared with conventional controllers.
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© 2019 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Sun, Q., Ren, H., Duan, Y., Yan, Y. (2019). The Adaptive PID Controlling Algorithm Using Asynchronous Advantage Actor-Critic Learning Method. In: Song, H., Jiang, D. (eds) Simulation Tools and Techniques. SIMUtools 2019. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 295. Springer, Cham. https://doi.org/10.1007/978-3-030-32216-8_48
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DOI: https://doi.org/10.1007/978-3-030-32216-8_48
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