Improvement of Induction Motor State Observation: Extended Kalman Filter Versus Adaptive Luenberger Observer

Author:

Zahraoui Yassine1,Akherraz Mohamed1,Elbadaoui Sara1

Affiliation:

1. Mohammed 5 University, Mohammadia School of Engineering, Department of Electrical Engineering, Agdal Rabat, MOROCCO

Abstract

the sensor-less control is a major issue in control domain. The use of sensors has several downsides like high cost, fragility and low reliability. Furthermore, the physical environment sometimes, does not allow to use sensors. Due to the multiple variables and non-linearity of induction motor dynamics, the estimation of the rotor speed and flux without the measurement is still a very challenging subject. The main objective of this paper is to present a comparative study between two observer’s structures, a full order adaptive observer based on Lyapunov theory and inherently extended Kalman filter which did not take the speed as adaptive quantity. Both of them are linked to a vector controlled induction motor drive. The effectiveness and estimation accuracy is investigated in detail by simulation results.

Publisher

World Scientific and Engineering Academy and Society (WSEAS)

Subject

Artificial Intelligence,General Mathematics,Control and Systems Engineering

Reference20 articles.

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3. Y. Zahraoui, M. Akherraz and C. Fahassa, Induction motor DTC performance improvementby reducing torque ripples in low speed, UPBSci. Bull. Ser. C, vol. 81, no 3, pp. 249–260,2019.

4. Y. Zahraoui, M. Akherraz, C. Fahassa and S. El-badaoui, Induction motor harmonic reduction using space vector modulation algorithm, Bulletin of Electrical Engineering and Informatics,vol. 9, no 2, 2020.

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