ADAPTIVE MODEL FOR THREE-PHASE INDUCTION MOTOR USING NEURAL NETWORK | ||
| ERJ. Engineering Research Journal | ||
| Article 4, Volume 30, Issue 2, April 2007, Pages 143-148 PDF (385.41 K) | ||
| Document Type: Original Article | ||
| DOI: 10.21608/erjm.2007.70049 | ||
| Author | ||
| Mahmoud M. EL-kholy | ||
| Electrical Power andMachines Department, Faculty of Engineering, Zagazig University, Zagazig, Egypt | ||
| Abstract | ||
| This paper proposes a method for the modeling of induction motor using neural networks. The use of artificial neural networks (ANN) in this paper is due to their benefits such as fast computation, ability of implementation, and easy interpolation. The neural network is trained by an experimental data over a wide range of voltages, frequencies and load torques. At each value of frequency and applied voltage the motor is loaded from no-load to full load. Therefore, the training data cover all the possible operating range of the motor under different frequencies and voltages. The advantages of the proposed model using ANN, is that the knowledge of the electrical parameters of the motor is not necessary, and the change in these parameters with operating conditions doesn't effect on performance of motor model. The inputs of the ANN motor model are voltage, frequency and current and the model gives the motor speed, torque and efficiency as the outputs. By these three values another motor performance characteristics can be calculated. The proposed model with (ANN) can be used in speed and torque sensorless estimation depending on the motor inputs, which will give an efficient and better performance for an induction motor. | ||
| Keywords | ||
| Induction motors; induction motor modeling; induction motor control; induction motor variable speed and artificial neural networks | ||
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