Robust nonlinear receding-horizon control of induction motors

Nonlinear robust receding-horizon control is designed and applied to fifth-order model of induction motor in cascade structure. The controller is based on a finite horizon continuous time minimization of the predicted tracking errors and no online optimization is needed. The initial system is decomposed into two sub-systems (mechanical and electromagnetic sub-systems) in cascade form. An integral action is incorporated in external loop to increase the robustness of the controller with respect to unknown time-varying load torque and mechanical parameters uncertainties. The control uses only measurement of the rotor speed and stator currents. The rotor flux is estimated by Kalman filter. The proposed nonlinear controller permits to achieve asymptotic speed and flux tracking in presence of mechanical parameters uncertainties, unknown variable load torque and resistances variations. In addition, it assures asymptotic decoupling of the speed and flux subsystems. The controller is applied, via simulation, to a benchmark example.