NDLI: Adaptive Speed Control for Brushless DC Motors Based On Genetic Algorithm and RBF Neural Network

Content Provider	IEEE Xplore Digital Library
Author	Yingfa Wang Changliang Xia Maohua Zhang Dan Liu
Copyright Year	2007
Description	Author affiliation: Tianjin Univ, Tianjin (Yingfa Wang; Changliang Xia; Maohua Zhang; Dan Liu)
Abstract	The brushless DC motors (BLDCM) are a multi-variable and non-linear system, so the research about the high performance of BLDCM is important, especially the control methods based on neural network. To solve the deficiency of neural network such as decision of structure and adjustment of parameters in hidden-unit, this paper presents an adaptive speed control approach based on genetic algorithm tuning radial basis function (RBF) neural network controller for brushless DC motor. In this approach, the RBF neural network whose structure and parameters of hidden-unit have been trained by genetic algorithm off-line constitutes a speed loop controller. The controller tunes parameters of neural network adaptively via the self-modifiability of network on-line, while the motor is running. At the same time, the current loop controller traces the change of given current rapidly, so that the system can adapt to variational environment. The results of experiments prove that the approach has lots of good performances in response speed, control accuracy, adaptability and robust.
Starting Page	1219
Ending Page	1222
File Size	2122418
Page Count	4
File Format	PDF
ISBN	9781424408177
DOI	10.1109/ICCA.2007.4376554
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-05-30
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Programmable control Adaptive control Velocity control Brushless DC motors Genetic algorithms Neural networks Control systems Nonlinear control systems DC motors Robust control Adaptive Control Brushless DC motors(BLDCM) Radial Basis Function(RBF) Genetic Algorithm
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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