Robust sliding-mode control for induction motor drive with RBF neural network based rotor speed estimation

In this paper, a speed estimation and control strategy for induction motor drive based on an indirect field-oriented control is presented. The rotor speed estimator based on a RBF neural network utilizes stator voltage and current measured values to calculate the rotor speed, and the control approach based on a sliding-mode controller with an integral sliding surface is proposed in order to regulate the induction motor speed. The stability analysis of the proposed control approach under parameter variations and load disturbances is provided using the Lyapunovpsilas stability arguments. The simulation results show that the presented controller with the proposed estimator provides high-performance dynamic characteristics and that this approach is robust with respect to plant parameter uncertainties and external load disturbances.