Robust Backstepping Control of Linear Induction Motor with Primary End Effect using Artificial Neural Networks

This paper presents a robust nonlinear controller for speed and flux control of a linear induction motor (LIM) drive with taking the primary end effect into account. An ideal nonlinear controller is first designed based on adaptive backstepping control approach for LIM low and high speed operation. Then the backstepping control and artificial neural networks (ANN ) are combined in order to design a robust nonlinear controller that is capable of preserving the drive system robustness subject to all parameter variations and uncertainties. The overall system stability is proved by Lyapunov theory. Finally, The effectiveness and validity of the proposed controller is supported by computer simulation results.