Title :
Study of the flux observer and its optimizing strategy for induction motor based on Extended Kalman Filter
Author :
Yongjun, Zhang ; Jing, Wang ; He, Chuan
Author_Institution :
Instn. of Inf. Eng., Univ. of Sci. & Technol., Beijing
Abstract :
A flux linkage estimation method for induction motor based on extended Kalman filter theory (EKF) is presented in this paper. In order to improve the accuracy of filtering, genetic algorithm (GA) is introduced to optimize the noise matrix, and also filtering parameters in EKF. Simulation results show that the flux observer with optimized filtering parameter has better estimation accuracy and dynamic performance at low speed.
Keywords :
Kalman filters; genetic algorithms; induction motors; machine control; matrix algebra; power filters; torque control; direct torque control; extended Kalman filter; flux linkage estimation method; flux observer; genetic algorithm; induction motor control; noise matrix optimisation; Couplings; Filtering; Genetic algorithms; Induction motors; Low pass filters; Nonlinear equations; State estimation; Stators; Uncertainty; Voltage;
Conference_Titel :
Electrical Machines and Systems, 2008. ICEMS 2008. International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-3826-6
Electronic_ISBN :
978-7-5062-9221-4
