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

Joint Authors

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

Source

Abstract and Applied Analysis

Issue

Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-7, 7 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2014-07-24

Country of Publication

Egypt

No. of Pages

7

Main Subjects

Mathematics

Abstract EN

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.

American Psychological Association (APA)

Zhong, Yuanchang& Huang, Xu& Meng, Pu& Li, Fachuan. 2014. PSO-RBF Neural Network PID Control Algorithm of Electric Gas Pressure Regulator. Abstract and Applied Analysis،Vol. 2014, no. 2014, pp.1-7.
https://search.emarefa.net/detail/BIM-1033968

Modern Language Association (MLA)

Zhong, Yuanchang…[et al.]. PSO-RBF Neural Network PID Control Algorithm of Electric Gas Pressure Regulator. Abstract and Applied Analysis No. 2014 (2014), pp.1-7.
https://search.emarefa.net/detail/BIM-1033968

American Medical Association (AMA)

Zhong, Yuanchang& Huang, Xu& Meng, Pu& Li, Fachuan. PSO-RBF Neural Network PID Control Algorithm of Electric Gas Pressure Regulator. Abstract and Applied Analysis. 2014. Vol. 2014, no. 2014, pp.1-7.
https://search.emarefa.net/detail/BIM-1033968

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-1033968