Optimized adaptive sliding-mode position control system for linear induction motor drive

This paper proposes an optimized adaptive position control system applied for a linear induction motor (LIM) drive taking into account the longitudinal end effects and uncertainties including the friction force. The dynamic mathematical model of an indirect field-oriented LIM drive is firstly derived for controlling the LIM. On the basis of a backstepping control law, a sliding mode controller (SMC) with embedded fuzzy boundary layer is designed to compensate the lumped uncertainties during the tracking control of periodic reference trajectories. Since it is difficult to obtain the bound of lumped uncertainties in advance in practical applications, an adaptive tuner based on the sense of Lyapunov stability theorem is derived to adjust the fuzzy boundary parameters in real-time. It is a quite complicated process of parameter tuning, especially for the proposed controller, due to the difficulty arisen from lacking of the accurate mathematical model of a system accompanied with unknown disturbance. Therefore, the soft-computing technique is adopted for off-line optimizing the controller parameters. The effectiveness of the proposed control scheme is validated through simulations and experiments for several scenarios. Finally, the advantages of performance improvement and robustness are illustrated at the end of the optimization procedure.