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In this paper, two different model reference adaptive systems (MRASs) based on the rotor-flux and the instantaneous reactive power errors for the speed estimation of an induction motor (IM) drive are compared from the stability point of view. The rotor-flux error based MRAS (RF-MRAS) involves the computation of rotor flux for the estimation of rotor speed. This, however, suffers from the integrator...
This paper presents a comparative study between a wellknown instantaneous reactive power (Q) based MRAS (Q-MRAS) and a relatively new X-MRAS used for sensorless speed estimation of induction motor drive from the stability point of view. The instantaneous and steady state values of Q are considered to develop the reference and adaptive models respectively for the former whereas those of a fictitious...
In this paper an artificial neural network (ANN) based speed estimator is presented for vector-controlled squirrel cage induction motor (IM) drive. The drive is stable in all operating region and is independent of stator resistance variation. Stator currents, modified stator voltages (Reference values) with stator resistance adaption are used as input to the ANN and rotor speed is treated as the output...
The paper deals with a problem of speed estimation in a shaft sensorless field oriented control structure with induction motor that is based on neural modelling approach. Two different neural estimators were developed; one for observing the magnetic flux and the other one for observing motor angular speed. Structures of the artificial neural network estimators are based on measurable motor variables:...
Speed estimation in field-oriented vector control of induction motor depends on effective estimation of rotor flux. This paper proposes speed estimator using improved rotor flux estimator based on modified voltage model with a high orders low-pass filter (LPF) and a low-pass filter in series and an error compensator by rotor flux oriented current model. In the flux estimation based on voltage model,...
This paper presents a novel speed estimation algorithm for sensorless speed control in a direct stator flux orientation of an induction motor. The speed observation uses the stator currents and voltages as inputs and, contrary to what is proposed this last decade, is achieved in a reference frame linked to the stator current space vector. This leads to a simple equation for speed calculation which...
This paper presents system analysis, modeling and simulation of an electric vehicle with different sensorless control techniques. Indeed, sensorless control is considered to be a lower cost alternative than the position or speed encoder-based control of induction motors for an electric vehicle. Two popular sensorless control methods, namely, the Luenberger observer and the Kalman filter methods are...
This paper presents an improved speed sensorless vector control method for induction motors used in the field of electrical vehicle propulsion. The proposed method is based on the d-q axis dynamic model of the induction motor and an improved closed-loop flux observer, which can achieve precise rotor and stator flux estimation over a wide speed range. And then, a rotor-speed-estimation method, based...
As rotation speed is necessary for high-performance induction motor control, how to estimate the speed quickly and accurately is concerned by most scholars. On the analysis of theoretic invertibility of the induction motorpsilas mathematic model, a speed estimation based on neural networks inversion is proposed. The structure of multi-layer feed-forward neural network (MFNN) is trained by advanced...
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