You can view the full text of this article for free using the link below.

Title: Adaptive AI-based two-stage control for an induction machine drive

Authors: Vikas Kumar; Prerna Gaur; A.P. Mittal

Addresses: Div. of Instrumentation and Control Engineering, Netaji Subhas Institute of Technology (NSIT), Azad Hind Fauj Marg,, Sector-3, Dwarka, N. Delhi-110078, India ' Div. of Instrumentation and Control Engineering, Netaji Subhas Institute of Technology (NSIT), Azad Hind Fauj Marg,, Sector-3, Dwarka, N. Delhi-110078, India ' Netaji Subhas Institute of Technology (NSIT), Azad Hind Fauj Marg, Sector-3, Dwarka, N. Delhi-110078, India

Abstract: In this paper, a two-stage control strategy for speed control of an induction machine drive is investigated by establishing the current input model of an induction motor drive. In order to reduce the effect of machine parameter variations on the performance of the drive, AI-based adaptive neuro-fuzzy controller is implemented to act on both slip frequency and current magnitude. The effect of the load torque variations and rotor resistance variations is observed for the controller.

Keywords: neuro-fuzzy control; fuzzy control; fuzzy logic; neural networks; current input models; two-stage control; adaptive control; speed control; induction machine drives; induction motors; controller design; load torque; rotor resistance.

DOI: 10.1504/IJCAD.2013.057458

International Journal of Circuits and Architecture Design, 2013 Vol.1 No.1, pp.74 - 88

Received: 23 Jan 2013
Accepted: 30 May 2013

Published online: 30 Oct 2013 *

Full-text access for editors Access for subscribers Free access Comment on this article