This paper investigates a novel model- predictive control strategy to control an induction motor fed by a matrix converter with multi-objective control capability. The proposed control method combines the features of the classical Model Predictive Control and the Space Vector Modulation technique into a Modulated Model Predictive Control. This new solution maintains all the characteristics of Model Predictive Control (such as fast transient response, multi-objective control using only one feedback loop, easy inclusion of nonlinearities and constraints of the system, the flexibility to include other system requirements in the controller) adding the advantages of working at fixed switching frequency and improving the quality of the controlled waveforms. Simulation results employing the control method to control the stator current and input reactive power of a direct matrix converter induction motor drive are presented. © 2015 IEEE.

Current control and reactive power minimization of a direct matrix converter induction motor drive with Modulated Model Predictive Control

Zanchetta P.
;
2016-01-01

Abstract

This paper investigates a novel model- predictive control strategy to control an induction motor fed by a matrix converter with multi-objective control capability. The proposed control method combines the features of the classical Model Predictive Control and the Space Vector Modulation technique into a Modulated Model Predictive Control. This new solution maintains all the characteristics of Model Predictive Control (such as fast transient response, multi-objective control using only one feedback loop, easy inclusion of nonlinearities and constraints of the system, the flexibility to include other system requirements in the controller) adding the advantages of working at fixed switching frequency and improving the quality of the controlled waveforms. Simulation results employing the control method to control the stator current and input reactive power of a direct matrix converter induction motor drive are presented. © 2015 IEEE.
2016
9781509017171
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11571/1372938
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