PSO-RBF Neural Network PID Control Algorithm of Electric Gas Pressure Regulator
Joint Authors
Zhong, Yuanchang
Li, Fachuan
Huang, Xu
Meng, Pu
Source
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
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