Title :
Speed control of induction motor without rotational transducers
Author :
Ben-Brahim, Lazhar ; Tadakuma, Susumu
Author_Institution :
Fac. of Technol., Qatar Univ., Doha, Qatar
Abstract :
This paper describes a newly developed speed sensorless induction motor drive control scheme based on neural network techniques. The backpropagation neural network technique is used to provide a real-time adaptive identification of the motor speed. The estimation objective is defined in terms of a desired or target trajectory that the neural networks model output should match or trade as closely as possible. The backpropagation algorithm is used to adjust the motor speed so that the neural model output follows the target trajectory. This backpropagation mechanism 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 analysed.
Keywords :
backpropagation; control system synthesis; induction motor drives; machine testing; machine vector control; neurocontrollers; parameter estimation; variable speed drives; velocity control; backpropagation mechanism; backpropagation neural network; control design; control performance; induction motor drive; neural model output; real-time adaptive parameter identification; speed sensorless control scheme; target trajectory; zero speed crossing phenomena; Backpropagation algorithms; Biological neural networks; Induction motors; Multi-layer neural network; Neural networks; Rotors; Stators; Trajectory; Transducers; Velocity control;
Conference_Titel :
Industry Applications Conference, 1998. Thirty-Third IAS Annual Meeting. The 1998 IEEE
Conference_Location :
St. Louis, MO, USA
Print_ISBN :
0-7803-4943-1
DOI :
10.1109/IAS.1998.732393