Title :
A new algorithm for flux and speed estimation in induction machine
Author :
Wenqiang, Yang ; Zhengchun, Jia ; Qiang, Xu
Author_Institution :
Huazhong Univ. of Sci. & Technol., Wuhan, China
Abstract :
A new reduced-order extended Kalman filter to estimate the rotor flux components and speed of an induction machine for speed sensorless vector control is proposed. With this method, two rotor flux components are selected as the state variables, and the rotor speed as an estimated parameter is regarded as an augmented state variable. The algorithm with reduced order decreases the computational complexity and makes the proposed estimator feasible to be implemented in real time. The simulation results show high accuracy of the estimation algorithm, and verify the usefulness of the proposed algorithm
Keywords :
Kalman filters; angular velocity control; induction motor drives; machine vector control; magnetic flux; parameter estimation; rotors; augmented state variable; computational complexity decrease; reduced-order extended Kalman filter; rotor flux components estimation; speed estimation; speed sensorless vector control; vector-controlled induction motor drives; Equations; Inductance; Induction machines; Induction motors; Machine vector control; Noise reduction; Parameter estimation; Rotors; State estimation; Stators;
Conference_Titel :
Electrical Machines and Systems, 2001. ICEMS 2001. Proceedings of the Fifth International Conference on
Conference_Location :
Shenyang
Print_ISBN :
7-5062-5115-9
DOI :
10.1109/ICEMS.2001.971772
