Tuning the stator resistance of induction motors using artificial neural network
- Univ. of Akron, OH (United States). Dept. of Electrical Engineering
Tuning the stator resistance of induction motors is very important, especially when it is used to implement direct torque control (DTC) in which the stator resistance is a main parameter. In this paper, an artificial network (ANN) is used to accomplish tuning of the stator resistance of an induction motor. The parallel recursive prediction error and backpropagation training algorithms were used in training the neural network for the simulation and experimental results, respectively. The neural network used to tune the stator resistance was trained on-line, making the DTC strategy more robust and accurate. Simulation results are presented for three different neural-network configurations showing the efficiency of the tuning process. Experimental results were obtained for the one of the three neural-network configuration. Both simulation and experimental results showed that the ANN have tuned the stator resistance in the controller to track actual resistance of the machine.
- OSTI ID:
- 538087
- Journal Information:
- IEEE Transactions on Power Electronics, Vol. 12, Issue 5; Other Information: PBD: Sep 1997
- Country of Publication:
- United States
- Language:
- English
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