Nonlinear control for linear induction motor servo drive

This paper describes a newly designed nonlinear control strategy to control a linear induction motor servo drive for periodic motion. Based on the concept of the nonlinear state feedback theory and optimal technique, a nonlinear control strategy, which is composed of an adaptive optimal control system and a sliding-mode flux observation system, is developed to improve the drawbacks in previous works concerned with complicated intelligent control. The control and estimation methodologies are derived in the sense of Lyapunov theorem so that the stability of the control system can be guaranteed. The sliding-mode flux observation system is implemented using a digital signal processor with a high sampling rate to make it possible to achieve good dynamics. Computer simulations and experimental results have been conducted to validate the effectiveness of the proposed control scheme under the occurrence of possible uncertainties and different reference trajectories. The merits of the proposed control system are indicated in comparison with a traditional optimal control system.