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

Author

Listed:
  • Yuanchang Zhong
  • Xu Huang
  • Pu Meng
  • Fachuan Li

Abstract

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.

Suggested Citation

  • Yuanchang Zhong & Xu Huang & Pu Meng & Fachuan Li, 2014. "PSO-RBF Neural Network PID Control Algorithm of Electric Gas Pressure Regulator," Abstract and Applied Analysis, Hindawi, vol. 2014, pages 1-7, July.
    • Handle: RePEc:hin:jnlaaa:731368
    DOI: 10.1155/2014/731368
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    Cited by:

    1. Guo, Pengteng & Shi, Qiqing & Jian, Zeng & Zhang, Jing & Ding, Qun & Yan, Wenhao, 2024. "An intelligent controller of homo-structured chaotic systems under noisy conditions and applications in image encryption," Chaos, Solitons & Fractals, Elsevier, vol. 180(C).

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