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A nonlinear adaptive control algorithm is proposed for induction machines. It is based on a two time-scale observer that allows the on-line identification of three critical uncertain parameters, i.e., load torque and motor stator and rotor resistances. In addition, the set-point of the rotor flux is adjusted in order to minimize the Joule losses and to improve the power efficiency. Experimental results...
This paper presents an on-line estimation for the stator resistances of the induction motor in the direct torque controlled drive, using artificial neural networks. The variation of stator resistance due to changes in temperature or frequency degrades the performance of such control strategy. In order to solve this issue, a backpropagation algorithm is used for training of the neural network. The...
Thermal protection is one of the most important aspects of any motor control system. This paper proposes a stator winding temperature estimation method for the thermal protection of inverter-fed electric motors. By modifying the space vector pulse width modulation (SVPWM) in an open-loop motor drive, a dc voltage can be intermittently injected into the motor. The stator temperature can be estimated...
The paper presents an experimental comparison of the efficiency and losses characteristics of 3 hp Premium efficiency and EFF1 induction motors. North American and European motors were tested according to Standard IEEE 112-B. A comparison, at rated operating point, shows that, under the same load conditions, the Premium motor operates with 2 % higher efficiency than EFF1 motor. However, in low voltage...
This paper presents application of adaptive neuro-fuzzy inference system (ANFIS) into a squirrel cage induction machine towards modeling, control and estimation. This paper contributes (i) Development of a simple and more realistic model of the induction motor using ANFIS. Using ANFIS, the parameter sets of the motor model are estimated. The simplified model contains eleven estimated parameters. In...
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