Sensorless low/zero speed control of induction motors with EKF estimation

Murat Barut; Seta Bogosyan; Metin Gokasan

Sensorless low/zero speed control of induction motors with EKF estimation

Murat Barut, Seta Bogosyan^*, Metin Gokasan

^*Corresponding author for this work

Department of Control and Automation Engineering

University of Alaska Fairbanks

Research output: Contribution to journal › Article › peer-review

1 Citation (Scopus)

Abstract

This study aims an improved estimation performance for the speed sensorless control of induction motors (IMs) over a very low/zero speed range. For this purpose, an Extended Kalman Filter (EKF) observer is designed to overcome the difficulties of flux/speed estimation at and around zero speed. The estimation problems related to low speed operation are further emphasized due to stator resistance, R_s uncertainties. Thus, the observer is designed to estimate the stator resistance, load torque and velocity, which is taken into account via the equation of motion. With this approach, the rotor flux information is reflected to the stator, thus improving the estimation accuracy. The simulation results obtained for the EKF approach in combination with the Direct Vector Control (DVC) of an IM, indicate improved performance.

Original language	English
Pages (from-to)	2530-2535
Number of pages	6
Journal	WSEAS Transactions on Systems
Volume	5
Issue number	11
Publication status	Published - Nov 2006

Keywords

EKF
Sensorless low/zero control
Stator resistance and load torque estimation

Cite this

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title = "Sensorless low/zero speed control of induction motors with EKF estimation",

abstract = "This study aims an improved estimation performance for the speed sensorless control of induction motors (IMs) over a very low/zero speed range. For this purpose, an Extended Kalman Filter (EKF) observer is designed to overcome the difficulties of flux/speed estimation at and around zero speed. The estimation problems related to low speed operation are further emphasized due to stator resistance, Rs uncertainties. Thus, the observer is designed to estimate the stator resistance, load torque and velocity, which is taken into account via the equation of motion. With this approach, the rotor flux information is reflected to the stator, thus improving the estimation accuracy. The simulation results obtained for the EKF approach in combination with the Direct Vector Control (DVC) of an IM, indicate improved performance.",

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author = "Murat Barut and Seta Bogosyan and Metin Gokasan",

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T1 - Sensorless low/zero speed control of induction motors with EKF estimation

AU - Barut, Murat

AU - Bogosyan, Seta

AU - Gokasan, Metin

PY - 2006/11

Y1 - 2006/11

N2 - This study aims an improved estimation performance for the speed sensorless control of induction motors (IMs) over a very low/zero speed range. For this purpose, an Extended Kalman Filter (EKF) observer is designed to overcome the difficulties of flux/speed estimation at and around zero speed. The estimation problems related to low speed operation are further emphasized due to stator resistance, Rs uncertainties. Thus, the observer is designed to estimate the stator resistance, load torque and velocity, which is taken into account via the equation of motion. With this approach, the rotor flux information is reflected to the stator, thus improving the estimation accuracy. The simulation results obtained for the EKF approach in combination with the Direct Vector Control (DVC) of an IM, indicate improved performance.

AB - This study aims an improved estimation performance for the speed sensorless control of induction motors (IMs) over a very low/zero speed range. For this purpose, an Extended Kalman Filter (EKF) observer is designed to overcome the difficulties of flux/speed estimation at and around zero speed. The estimation problems related to low speed operation are further emphasized due to stator resistance, Rs uncertainties. Thus, the observer is designed to estimate the stator resistance, load torque and velocity, which is taken into account via the equation of motion. With this approach, the rotor flux information is reflected to the stator, thus improving the estimation accuracy. The simulation results obtained for the EKF approach in combination with the Direct Vector Control (DVC) of an IM, indicate improved performance.

KW - EKF

KW - Sensorless low/zero control

KW - Stator resistance and load torque estimation

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JF - WSEAS Transactions on Systems

IS - 11

ER -

Sensorless low/zero speed control of induction motors with EKF estimation

Abstract

Keywords

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