Adaptive Supervisory of Induction Motor Starting by Artificial Neural Networks

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 algoritlmr. The reference data as tracking trajectory computed from the model referennnnnnnnnnnnnnnnnnnnnce 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.keywords: artificial neural network controller(ANNC), model reference adaptive of induction motor starting(MRAIMS), starting speed