A predictive control framework for 3-phase induction motors modeled in natural variables

摘要

This paper presents a nonlinear control approach for 3-phase induction motors. The proposed structure combines a 3-phase predictive controller with an integrative reference filter. The predictive controller is designed based on an induction motor model established in natural variables (without using transformations), which is a nonlinear and time-variant one. This model enables the controller to work independently with the supply voltages, considering unbalanced situations. A dynamic evaluation of the state equation coefficients is used to perform the process variables prediction, thereby executing a point-to-point linearization. The conversion of the rotation speed and stator flux modulus reference values is realized by a integrative 3-phase referrer, which acts as a reference filter, expressing the references as 3-phase signals and acting as an integrator to eliminate steady-state errors. Also, a constraint feature is implemented, to reduce the currents. Simulation results satisfactorily show the proposed control architecture characteristics for various reference values and for motor operation as a brake and with load variation.