Title: Neural network augmented backstepping control for an induction machine
Author: Mohammed Belkheiri, Fares Boudjema
Department of Electrical Engineering, University of Amar Thelidji, Laghouat BP G37, Algeria.
Process Control Research Laboratory, Ecole Nationale Polytechnique (ENP), Elharrach, Algiers BP 162, Algeria
Abstract: A new control approach is proposed to address the tracking problem of an induction machine based on a modified Field-Oriented Control (FOC) method. In this approach, one relies first on a partially known model to the system to be controlled using a backstepping control strategy. The obtained controller is then augmented by an Adaptive Neural Network (NN) that serves as an approximator for the neglected dynamics and modelling errors. The proposed approach is systematic, and exploits the known non-linear dynamics to derive the stepwise virtual stabilising control laws. At the final step, an augmented Lyapunov function is introduced to derive the adaptation laws of the network weights. The effectiveness of the proposed controller is demonstrated through computer simulation.
Keywords: induction machines; nonlinear control; adaptive control; FOC; field-oriented control; backstepping control; NNs; neural networks; simulation; tracking control.
Int. J. of Modelling, Identification and Control, 2008 Vol.5, No.4, pp.288 - 296
Available online: 25 Feb 2009