State estimation of induction motor using unscented Kalman filter

Akin B., Orguner U., Ersak A.

IEEE Conference on Control Applications, İstanbul, Turkey, 23 - 25 June 2003, pp.915-919 identifier identifier

  • Publication Type: Conference Paper / Full Text
  • City: İstanbul
  • Country: Turkey
  • Page Numbers: pp.915-919
  • Keywords: induction motor, speed estimation, UKF, EKF, sensorless vector control, state observer, SPEED IDENTIFICATION, VECTOR CONTROL
  • Middle East Technical University Affiliated: Yes

Abstract

In this paper, a new estimation technique, unscented Kalman filter (UKF) is applied to state observation in field oriented control (FOC) of induction motor. UKF, a recent derivative-free nonlinear estimation tool, is used for estimating rotor speed and fluxes using sensed stator current and voltages. In the simulations, UKF, whose several intrinsic properties suggest its use over EKF in highly nonlinear systems, turned out to be very similar to EKF in flux estimates. The simulation results also show that UKF has slightly better speed estimation performance than EKF while driven under the identical machine model and parameters (covariances).