Neural network augmented backstepping control for an induction machine

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.

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