Design a PID Controller for Suspension System by Back Propagation Neural Network
Joint Authors
Source
Issue
Vol. 2013, Issue 2013 (31 Dec. 2013), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2013-02-24
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Abstract EN
This paper presents a neural network for designing of a PID controller for suspension system.
The suspension system, designed as a quarter model, is used to simplify the problem to one-dimensional spring-damper system.
In this paper, back propagation neural network (BPN) has been used for determining the gain parameters of a PID controller for suspension system of automotive.
The BPN method is found to be the most accurate and quick.
The best results were obtained by the BPN by Levenberg-Marquardt algorithm training with 10 neurons in the one hidden layer.
Training was continued until the mean squared error is less than 1e−5.
Desired error value was achieved in the BPN, and the BPN was tested with both data used and not used for training.
By training of this network, it is possible to estimate the gain parameters of PID controller at any condition.
The inputs of network are automotive velocity, overshoot percentage, settling time, and steady state error of suspension system response.
Also outputs of the net are the gain parameters of PID controller.
Resultant low relative error value of the ANN model indicates the usability of the BPN in this area.
American Psychological Association (APA)
Haydari, Muhammad& Homaei, Hadi. 2013. Design a PID Controller for Suspension System by Back Propagation Neural Network. Journal of Engineering،Vol. 2013, no. 2013, pp.1-9.
https://search.emarefa.net/detail/BIM-470929
Modern Language Association (MLA)
Haydari, Muhammad& Homaei, Hadi. Design a PID Controller for Suspension System by Back Propagation Neural Network. Journal of Engineering No. 2013 (2013), pp.1-9.
https://search.emarefa.net/detail/BIM-470929
American Medical Association (AMA)
Haydari, Muhammad& Homaei, Hadi. Design a PID Controller for Suspension System by Back Propagation Neural Network. Journal of Engineering. 2013. Vol. 2013, no. 2013, pp.1-9.
https://search.emarefa.net/detail/BIM-470929
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-470929