A predictive control framework for 3‐phase induction motors modeled in natural variables. (1st February 2017)

• Record Type: Journal Article
• Authors: Bonci Cavalca, Eduardo; Nied, Ademir; Santos Matos Cavalca, Mariana; de Oliveira, José
• Is Part Of: Optimal control applications and methods. Volume 38:Number 6(2017)
• Page Start: 1014
• Page End: 1021
• Publication Date: 2017-02-01
• Subjects: induction motor -- predictive control -- 3‐phase systems; Control theory -- Periodicals; Mathematical optimization -- Periodicals; 629.8312
• DOI: 10.1002/oca.2307
• Languages: English
• ISSNs: 0143-2087

Abstract

Summary: 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.