Nonlinear Multivariable Control of Induction Motor based on Generalized Predictive Control

A. Merabet, M. Ouhrouche, R.-T. Bui, and J.S. Thongam (Canada)


Nonlinear system, generalized predictive control, and induction motor drive.


A nonlinear generalized predictive control (NGPC) of induction motor drive is presented. The predictive control algorithm is implemented using a model of the motor in fixed stator reference frame (α-β). The task of the controller is to track the desired speed and flux profiles. Rotor flux information required to implement the predictive control algorithm is estimated using Kalman Filter algorithm. The NGPC law minimizes a simple quadratic cost function of the predicted tracking error following the receding horizon strategy. Its implementation does not need an on line optimization, and the closed loop dynamics under this nonlinear predictive controller depends on design parameters (prediction times and control order). Simulations are carried out in order to show the effectiveness of the proposed method for high dynamic performance applications of induction motor drive.

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