DocumentCode
2012151
Title
Internal Model Control of PM Synchronous Motor Based on RBF Network optimized by Genetic Algorithm
Author
Yu-Zhou, Li ; Yu-Tao, Luo ; Ke-Gan, Zhao ; Li Jim
Author_Institution
South China Univ. of Technol., Guangzhou
fYear
2007
fDate
May 30 2007-June 1 2007
Firstpage
3051
Lastpage
3054
Abstract
An internal model control method which is based on RBF network optimized by genetic algorithm is proposed to control the speed of the permanent magnet synchronous motor in this paper. As genetic algorithm is a global search and optimization algorithm which simulates the genetic and long-term evolvement process of biology. By the optimization of genetic algorithm, the optimal structure and parameters of the RBF network are achieved and the optimized RBF network is applied into the speed loop internal model control of the permanent magnet synchronous motor. Simulation results show that the proposed internal model controller can overcome the influence caused by nonlinear factor and time varying parameters, and provides the high-performance dynamic characteristics.
Keywords
genetic algorithms; machine control; neurocontrollers; permanent magnet motors; radial basis function networks; synchronous motors; velocity control; RBF network; genetic algorithm; internal model control; permanent magnet synchronous motor; speed control; AC motors; Artificial neural networks; Biological system modeling; Control systems; Equations; Genetic algorithms; Permanent magnet motors; Radial basis function networks; Sliding mode control; Synchronous motors; PMSM; RBF network; genetic algorithm; internal model control; speed control;
fLanguage
English
Publisher
ieee
Conference_Titel
Control and Automation, 2007. ICCA 2007. IEEE International Conference on
Conference_Location
Guangzhou
Print_ISBN
978-1-4244-0817-7
Electronic_ISBN
978-1-4244-0818-4
Type
conf
DOI
10.1109/ICCA.2007.4376921
Filename
4376921
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