Design of Kalman Filter for induction motor drive

This paper compares the standard and extended versions of kalman filter for rotor flux estimation in a voltage source inverter fed vector controlled induction motor drive. The design method for the both versions of kalman filter is presented and shown. Only simulation results are presented in this p...

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Main Authors: Singh, K., Singh, M.
Format: Conference Proceeding
Language:English
Subjects:
Current measurement
Extended kalman filter
Gaussian noise
Induction motor parameters
Kalman filter
Kalman filters
Mathematical model
Noise
Noise measurement
On-line estimation
Rotors
Stators
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Singh, M.
description This paper compares the standard and extended versions of kalman filter for rotor flux estimation in a voltage source inverter fed vector controlled induction motor drive. The design method for the both versions of kalman filter is presented and shown. Only simulation results are presented in this paper. Methodology to create KF, EKF for online identification of induction motor parameters are also described in details. The Extended Kalman Filter can be used for combined state and parameter estimation by treating selected parameters as extra states and forming an augmented state vector. Depending on whether the original state space model is linear or not, the augmented model is nonlinear in multiplication of states. A fifth order augmented state space model is developed when the EKF is applied to the simultaneous estimation of states of stator and rotor d-q current and rotor d-q fluxes. Important conclusions, together with recommendations for observer selection.
doi_str_mv 10.1109/SCES.2013.6547575
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The design method for the both versions of kalman filter is presented and shown. Only simulation results are presented in this paper. Methodology to create KF, EKF for online identification of induction motor parameters are also described in details. The Extended Kalman Filter can be used for combined state and parameter estimation by treating selected parameters as extra states and forming an augmented state vector. Depending on whether the original state space model is linear or not, the augmented model is nonlinear in multiplication of states. A fifth order augmented state space model is developed when the EKF is applied to the simultaneous estimation of states of stator and rotor d-q current and rotor d-q fluxes. 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subjects Current measurement
Extended kalman filter
Gaussian noise
Induction motor parameters
Kalman filter
Kalman filters
Mathematical model
Noise
Noise measurement
On-line estimation
Rotors
Stators
title Design of Kalman Filter for induction motor drive
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