Implementation of EKF based sensorless drive system using vector controlled PMSM fed by a matrix converter

Aydoğmuş, Ömür; Sünter, Sedat

doi:10.1016/j.ijepes.2012.06.062

Cited by 40 publications

(25 citation statements)

References 28 publications

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“…The EKF uses the nonlinear motor model for speed estimation. EKF has been used in PMSM drives in a variable fashion (Aydogmus and Sünter, 2012;Xu et al, 2013).…”

Section: Introductionmentioning

confidence: 99%

Sensorless control of PMSM drive using extended Kalman filter and fuzzy logic controller

Hussain¹,

Bazaz²

2016

IJIED

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This paper describes the estimation and control of rotor speed of a permanent magnet synchronous motor (PMSM) drive. The estimation is done through the use of extended Kalman filter (EKF). The EKF uses the dynamic state space model of the PMSM to estimate the speed and fluxes through a set of mathematical equations. The mathematics of which is dependent on the knowledge of stator voltages and currents. Besides, a fuzzy logic controller (FLC) is used for speed control of PMSM in this paper that aids against load and speed variations. Also, space vector pulse width modulation (SVPWM) is implemented for optimal performance of the drive. Simulation of a 1.7 Nm, 220 Vdc, 3,750 rpm PMSM is presented in this paper and speed tracking is achieved under different operating conditions.

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“…The EKF uses the nonlinear motor model for speed estimation. EKF has been used in PMSM drives in a variable fashion (Aydogmus and Sünter, 2012;Xu et al, 2013).…”

Section: Introductionmentioning

confidence: 99%

Sensorless control of PMSM drive using extended Kalman filter and fuzzy logic controller

Hussain¹,

Bazaz²

2016

IJIED

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“…Usually, rotor speed can be directly measured using a sensor (an optical encoder) which is mounted on the motor shaft. However, the system cost, volume and weight of the motor are increased; also, the reliability of drive reduces with hard environments conditions [1,2]. Furthermore, it is not always possible to reach all the state variables in the considered system.…”

Section: Introductionmentioning

confidence: 99%

Particle swarm optimization of an extended Kalman filter for speed and rotor flux estimation of an induction motor drive

2014

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A novel method based on a combination of the extended Kalman filter with particle swarm optimization (PSO) to estimate the speed and rotor flux of an induction motor drive is presented. The proposed method will be performed in two steps. As a first step, the covariance matrices of state noise and measurement noise will be optimized in an off-line manner by the PSO algorithm. As a second step, the optimal values of the above covariance matrices are injected in our speed-rotor flux estimation loop (on-line). Computer simulations of the speed and rotor flux estimation have been performed to investigate the effectiveness of the proposed method. Simulations and comparison with genetic algorithms show that the results are very encouraging and achieve good performances.

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“…These observers are used to observe the flux and speed estimation in a closed loop [4] [6][7]. Although such approaches lead to different performance in relation to the degree of algorithmic and computational complexity, they generally offer good performance in a wide range of speed but cannot estimate very low speeds in a stable manner [8][9].…”

Section: Introductionmentioning

confidence: 99%

Reduced-Order Sliding Mode Observer-based Speed Sensorless Vector Control of Double Stator Induction Motor

2014

APH

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In this paper a reduced-order sliding mode observer-based speed sensorless vector control of a double stator induction motor (DSIM) is presented. The conventional reduced-order observer has large chattering on the speed and the torque. In order to solve this problem, the sliding mode technique with smooth function is used. The simulation testsshow the effectiveness of the proposed method especially in the load disturbances and/or the change of the reference speed.

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Implementation of EKF based sensorless drive system using vector controlled PMSM fed by a matrix converter

Cited by 40 publications

References 28 publications

Sensorless control of PMSM drive using extended Kalman filter and fuzzy logic controller

Sensorless control of PMSM drive using extended Kalman filter and fuzzy logic controller

Particle swarm optimization of an extended Kalman filter for speed and rotor flux estimation of an induction motor drive

Reduced-Order Sliding Mode Observer-based Speed Sensorless Vector Control of Double Stator Induction Motor

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