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A method of speed identification for sensorless induction motor (IM) drives based on a model reference adaptive system (MRAS) is proposed in this paper. The adaptive full-order observer based on IM equation is used to estimate stator currents and rotor flux. Lyapunovpsilas stability criterion is employed to estimate rotor speed. The same algorithm deduced from Lyapunovpsilas stability criterion is...
A scheme of a model reference adaptive system (MRAS) based on the theory of parameter optimization for the PMSM servo system is described in this paper. The scheme can promptly work out the speed of the rotor without any other position/speed sensor. Different from the other MRAS-based speed observers which constructed according the theory of stability customarily, by using the error between the measured...
This paper presents a novel model reference adaptive system (MRAS) speed observer for induction motor drives based on stator currents. The measured currents are used as reference model for the MRAS observer to avoid the use of a pure integrator. A two layer Neural Network (NN) stator current observer is used as the adaptive model which requires the rotor flux information. This can be obtained from...
Two different online parameter identification methods for doubly fed induction generators (DFIG) are investigated in this paper. A model reference adaptive system (MRAS) and a new approach for estimation of the inductances are introduced. Lyapunov stability theory is applied to the adaptive law of the MRAS method. This method requires a test signal which excites all systems eigenvalues. Therefore...
This paper presents a new adaptive scheme for online estimation of stator resistance in speed-sensorless induction motor drives. The method is based on the adaptive control theory of model reference adaptive system (MRAS) approach with Luenberger observer. And the stability of the observer with stator resistance estimation in sensorless vector control of induction motors is proved by the Lyapunov's...
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