Title :
Speed control of induction motor without rotational transducers
Author :
Ben-Brahim, Lazhar ; Tadakuma, Susumu ; Akdag, Alper
Author_Institution :
Dept. of Ind. Technol., Qatar Univ., Doha, Qatar
Abstract :
This paper describes a newly developed speed sensorless drive based on neural networks. A backpropagation neural 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 trajectory. Backpropagation forces the estimated speed to follow precisely the actual motor speed. The zero-speed crossing phenomena is also described, and experimental results are presented and analyzed
Keywords :
backpropagation; control system synthesis; induction motors; machine testing; machine theory; machine vector control; neurocontrollers; velocity control; backpropagation algorithm; backpropagation neural network; control design; control performance; induction motor speed control; real-time adaptive motor speed identification; rotational transducers; speed sensorless drive; zero-speed crossing phenomena; Backpropagation algorithms; Induction motors; Multi-layer neural network; Neural networks; Rotors; Stators; Supervised learning; Trajectory; Transducers; Velocity control;
Journal_Title :
Industry Applications, IEEE Transactions on