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Model predictive optimal control considering current and voltage limitations: Real-time validation using OPAL-RT technologies and five-phase permanent magnet synchronous machines

Article dans une revue avec comité de lecture
Author
BERMUDEZ GUZMAN, Mario
254694 Universidad de Sevilla = University of Seville
GOMOZOV, Oleg
BARRERO, Federico
254694 Universidad de Sevilla = University of Seville
ccSEMAIL, Eric
13338 Laboratoire d’Électrotechnique et d’Électronique de Puissance - ULR 2697 [L2EP]
ccKESTELYN, Xavier
175453 Arts et Métiers ParisTech
NGUYEN, Ngac Ky
25826 Modélisation, Intelligence, Processus et Système [MIPS]

URI
http://hdl.handle.net/10985/14556
DOI
10.1016/j.matcom.2018.07.005
Date
2019
Journal
Mathematics and Computers in Simulation

Abstract

Multiphase machines have recently gained interest in the research community for their use in applications where high power density, wide speed range and fault-tolerant capabilities are required. The optimal control of such drives requires the consideration of voltage and current limits imposed by the power converter and the machine. While conventional three-phase drives have been extensively analyzed taking into account such limits, the same cannot be said in the multiphase drives’ case. This paper deals with this issue, where a novel two-stage Model Predictive optimal Control (2S-MPC) technique is presented, and a five-phase permanent magnet synchronous multiphase machine (PMSM) is used as a case example. The proposed method first applies a Continuous-Control-Set Model Predictive Control (CCS-MPC) stage to obtain the optimal real-time stator current reference for given DC-link voltage and stator current limits, exploiting the maximum performance characteristics of the multiphase drive. Then, a Finite-Control-Set Model Predictive Control (FCS-MPC) stage is utilized to generate the switching state in the power converter and force the stator current tracking. An experimental validation of the proposed controller is finally provided using a real-time simulation environment based on OPAL-RT technologies.

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