Speed estimated for vector control of induction motor using reduced-order extended Kalman filter

Author

Ge, Qiongxuan ; Feng, Zhiyue

Author_Institution

Inst. of Electr. Eng., Acad. Sinica, Beijing, China

Volume

1

fYear

2000

fDate

2000

Firstpage

138

Abstract

This paper aims to study and develop a high performance vector control speed sensorless induction motor viable speed system. An Intel 8098 CPU and a high speed digital signal processing TMS320C30 chip are employed to construct a speed sensorless induction motor viable speed system. In order to get a high dynamic and static characteristic, two sets of error models are commutated to improve the accuracy of identification. Simulation and experiment results demonstrate that the reduced-order Kalman filter algorithm is both correct and efficient

Keywords

Kalman filters; control system analysis; control system synthesis; digital control; induction motors; machine testing; machine theory; machine vector control; parameter estimation; power engineering computing; velocity control; TMS320C30 DSP chip; control design; control simulation; dynamic characteristics; error models; identification; induction motor vector control; reduced-order Kalman filter algorithm; reduced-order extended Kalman filter; speed estimation; speed sensorless control; static characteristics; Error correction; Induction motors; Machine vector control; Noise measurement; Nonlinear equations; Q measurement; Rotors; Signal processing algorithms; Stators; Working environment noise;

fLanguage

English

Publisher

ieee

Conference_Titel

Power Electronics and Motion Control Conference, 2000. Proceedings. IPEMC 2000. The Third International

Conference_Location

Beijing

Print_ISBN

7-80003-464-X

Type

conf

DOI

10.1109/IPEMC.2000.885345

Filename

885345