Abstract and Applied Analysis

PSO-RBF Neural Network PID Control Algorithm of Electric Gas Pressure Regulator

Yuanchang Zhong, Xu Huang, Pu Meng, and Fachuan Li

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The current electric gas pressure regulator often adopts the conventional PID control algorithm to take drive control of the core part (micromotor) of electric gas pressure regulator. In order to further improve tracking performance and to shorten response time, this paper presents an improved PID intelligent control algorithm which applies to the electric gas pressure regulator. The algorithm uses the improved RBF neural network based on PSO algorithm to make online adjustment on PID parameters. Theoretical analysis and simulation result show that the algorithm shortens the step response time and improves tracking performance.

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Abstr. Appl. Anal., Volume 2014, Special Issue (2014), Article ID 731368, 7 pages.

First available in Project Euclid: 2 October 2014

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Zhong, Yuanchang; Huang, Xu; Meng, Pu; Li, Fachuan. PSO-RBF Neural Network PID Control Algorithm of Electric Gas Pressure Regulator. Abstr. Appl. Anal. 2014, Special Issue (2014), Article ID 731368, 7 pages. doi:10.1155/2014/731368. https://projecteuclid.org/euclid.aaa/1412278505

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