Speed Control of Induction Motor

This paper describes a newly developed speed sen- sorless drive based on neural networks. A backpropagation neu- ral network is used to provide real-time adaptive identification of the motor speed. The estimation objective is the sum of squared errors between a target trajectory and the neural network model output. A backpropagation algorithm is used to adjust the motor speed, so that the neural model output follows the target tra- jectory. Backpropagation forces the estimated speed to follow precisely the actual motor speed. The zero-speed crossing phe- nomena is also described, and experimental results are presented and analyzed.