A Predictive Algorithm for Controlling Speed and Rotor Flux of Induction Motor

Abstract

A model-based predictive control of rotor flux and speed of a vector-controlled induction motor (IM) is presented. A state-space approach is employed for modeling a rotor-flux-oriented IM. The control law is derived by optimization of an objective function that considers the control effort and the difference between the predicted outputs (speed and rotor flux) and the specific references, with predicted outputs calculated using a linearized state-space model. The rotor flux and speed are estimated by using an extended Kalman filter. In this model, the load inertia is unknown, and the external load torque is considered to be a disturbance. Its amplitude is computed with the electromechanical equation or estimated by the Kalman filter. Simulated and experimental results show the good performance of this strategy.