A predictive control framework for 3‐phase induction motors modeled in natural variables |
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Authors: | Eduardo Bonci Cavalca Ademir Nied Mariana Santos Matos Cavalca José de Oliveira |
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Institution: | Department of Electrical Engineering of the Technological Sciences Center, Santa Catarina State University (UDESC), Joinville, SC, Brazil |
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Abstract: | 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. |
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Keywords: | induction motor predictive control 3‐phase systems |
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