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
fDate :
May 30 2007-June 1 2007
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;
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
DOI :
10.1109/ICCA.2007.4376921