Title :
On-line parameter identification of asynchronous motor using improved least squares
Author :
Guo Jiantao ; Li Guoli ; Xie Fang ; Hu Cungang ; Pan Zhifeng ; Meng Nan
Author_Institution :
Sch. of Electr. Eng. & Autom., Anhui Univ., Hefei, China
Abstract :
The value of stator and rotor resistance, inductance is important to controller design and condition monitoring of an asynchronous motor system. This paper proposes an improved least squarest to identify the parameters of asynchronous motor. Instead of using signal of rotor magnetic linkage, we measuring the stator current, voltage and signal of rotational speed, made use of the method of forgetting factor recursive least squares to carry on recognizing motor parameters.
Keywords :
induction motors; least squares approximations; parameter estimation; rotors; stators; asynchronous motor; least squares; magnetic linkage; on-line parameter identification; rotor; stator; Educational institutions; Equations; Mathematical model; Parameter estimation; Rotors; Stator windings; asynchronous motor; forgetting factor recursive least squares; parameter identification;
Conference_Titel :
Industrial Electronics and Applications (ICIEA), 2014 IEEE 9th Conference on
Conference_Location :
Hangzhou
Print_ISBN :
978-1-4799-4316-6
DOI :
10.1109/ICIEA.2014.6931145
