KEYWORDS: Temperature control, Education and training, Mathematical modeling, Control systems, Online learning, Evolutionary algorithms, Technetium, Systems modeling, Design and modelling, Computer simulations
In this paper, an asynchronous advantage actor-critic (A3C) based intelligent temperature control method is proposed for Continuous Stirred Tank Reactor (CSTR) system. Firstly, the overall framework of CSTR system is composed of global network, thread network, environment model and interaction mechanism is designed. Secondly, the process of interaction is designed: the thread network is trained to interact with environmental models by using an asynchronous multi-threaded approach, the trained parameters are updated and synchronized to the global network. Finally, the effectiveness and stability of A3C algorithm is verified by the simulation experiments. The simulation experiments show that the trained A3C network can control the output temperature of the CSTR system to reach the preset temperature and keep it the preset temperature, so the temperature control of the CSTR system is achieved in the A3C algorithm.
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