Research on Pressurizer Pressure Control System Based on BP Neural Network Control of Self-Adjusted PID Parameters

Abstract:

The pressurizer is an important device in nuclear reactor system, and the traditional PID regulator is usually used to control pressure system of pressurizer in modern reactors. However, it is difficult to get precise parameters of traditional PID controller, and the PID control method is relied on the precise mathematical model badly. And the response of PID controller is often shown by the large amount of overshoot and long setting time which are not the desired results. For such a large inertia and complex time-varying control system, the tradition PID controller can not obtain the satisfy control results. A controller based on BP neural network in this paper has a simple structure, and the parameters of PID controller can be tuned on-line by the neural network self-learning characteristics. The computer simulation experiment demonstrates that the BP neural network PID controller performs very well when compared with the tradition PID regulator in minimal overshoot and more quick response.

• Periodical: Applied Mechanics and Materials (Volumes 291-294)
• Pages: 2416-2423
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.291-294.2416
• Online since: February 2013
• Authors: Guo Duo Zhang, Xu Hong Yang, Dong Qing Lu, Yong Xiao Liu
• Keywords: BP Neural Network (BPNN), PID Controller, Pressure Control System, Pressurizer, PWR-Type

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