Utilizing neural networks for dynamic performance improvement of induction motor drive: a fresh approach with the novel IP-self-tuning controller

This paper introduces a neural network adjustment method for a single gain of an integral proportional (IP) speed regulator, to improve the speed control of an induction motor. Thanks to its simplicity and strength, the integral proportional (IP) controller is widely used in the industry for speed control. Yet, in some cases, when the load or mechanical parameters change according to its working conditions, the integral proportional (IP) efficiency decreases, and the setup quality degrades. In this case, a neural IP-self-tuning seems to overcome these difficulties and ensure a good control performance. The results obtained through the implementation of the proposed control on a dSPACE system and an induction motor clearly demonstrate the effectiveness of this method.