Scalar control of an induction motor using a neural sensorless technique

• A neural-network-method applied to speed estimation in induction motor is presented.
• Sensorless scalar control using voltage source inverter with space vector modulation and p-PLL is presented.
• Simulation and experimental results with different mechanical loads are presented.
• Two different cases of neural network structure are presented.

The induction motor plays a key role in many industrial sectors, primarily due to its robustness and low cost. When the load coupled to the motor axis requires speed control, some of the drive and control strategies are based on the estimated axis speed of the motor. The direct measurement of this quantity reduces its robustness and increases the driver implementation cost. This paper proposes an alternative methodology for estimating the speed of a three phase induction motor driven by a voltage source inverter, using space vector modulation under the scalar control strategy and based on artificial neural networks. To validate the performance of the proposed method under motor load torque and speed reference set point variations, simulation and experimental results are presented.

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