Fuzzy logic based sensorless vector control of Induction motor

Author

Bindu, V. ; Unnikrishnan, A. ; Gopikakumari, R.

Author_Institution

Div. of Electron. Eng., Cochin Univ. of Sci. & Technol., Kochi, India

fYear

2012

fDate

7-9 Dec. 2012

Firstpage

514

Lastpage

518

Abstract

The paper describes an Extended Kalman filter (EKF) algorithm for the estimation of rotor speed of a squirrel cage induction motor from the measured line currents. Estimated speed values are used for closed loop control. The voltage control is performed under synchronously rotating reference frame and the estimated speed information is used for the reference frame transformation. The fuzzy logic principle is used to control the speed of the Induction motor.

Keywords

Kalman filters; angular velocity control; closed loop systems; fuzzy control; machine vector control; nonlinear filters; power filters; sensorless machine control; squirrel cage motors; EKF algorithm; closed loop control; extended Kalman filter algorithm; fuzzy logic based sensorless vector control; measured line currents; reference frame transformation; rotor speed estimation; speed control; squirrel cage induction motor; synchronously rotating reference frame; voltage control; Equations; Fuzzy logic; Induction motors; Kalman filters; Mathematical model; Niobium; Rotors; Extended Kalman filter; Fuzzy logic controller; Induction motor;

fLanguage

English

Publisher

ieee

Conference_Titel

India Conference (INDICON), 2012 Annual IEEE

Conference_Location

Kochi

Print_ISBN

978-1-4673-2270-6

Type

conf

DOI

10.1109/INDCON.2012.6420672

Filename

6420672