IEEJ Transactions on Electronics, Information and Systems
Online ISSN : 1348-8155
Print ISSN : 0385-4221
ISSN-L : 0385-4221
ADAPTIVE SUPERVISORY OF INDUCTION MOTOR STARTING BY ARTIFICIAL NEURAL NETWORKS
Mauridhi Hery PurnomoKazuo SHIGETAEiji SHIMIZU
Author information
JOURNAL FREE ACCESS

1996 Volume 116 Issue 12 Pages 1407-1413

Details
Abstract
This paper presents implementation of Artificial Neural Network Controller (ANNC) for induction motor starting, to track the reference condition scheme. To achieve mapping of the desired input/output we combine generally known method for control, the model reference adaptive system and the learning algoritlmm. The reference data as tracking trajectory computed from the model reference adaptive of induction motor starting (MRAIMS). A supervised learning neural network algorithm is used to return the induction motor starting speed (rotation starting) disturbance condition caused by the varies of load, back to the starting speed reference condition. The ANNC continuously monitors the status of the system parameter and the performance of motor starting, and the ANNC output is used as the current control signal of induction motor starting, because control of starting current, will improve the behavior of starting speed.
Content from these authors
© The Institute of Electrical Engineers of Japan
Previous article Next article
feedback
Top