Model Predictive Control for a Six-Phase PMSM Motor with a Reduced-Dimension Cost Function

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

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Original languageEnglish
Pages (from-to)969-979
Journal / PublicationIEEE Transactions on Industrial Electronics
Issue number2
Online published4 Mar 2019
Publication statusPublished - Feb 2020


This paper presents a model predictive control for a six-phase permanent magnet synchronous machine (PMSM) with a reduced-dimension cost function. Only the variables in the harmonic subspace are included into the cost function, while the energy conversion related variables are excluded. This is achieved by using the deadbeat direct torque and flux control (DB-DTFC) method to obtain a reference voltage vector and then to track the torque and stator flux properly in the energy conversion related subspace. Then, according to the position of the reference vector, the appropriate prediction vectors can be determined. Subsequently, a reduced-dimension cost function including only the harmonic constraints is defined to evaluate the feasible prediction vectors. In this way, the predictive model and the cost function are simplified without redundant constraints. Meanwhile, the torque and flux can be regulated satisfactorily, and the harmonic currents are suppressed effectively. Finally, experimental results of the proposed method and the conventional model predictive torque control (MPTC) are presented in this paper to verify the validity of the proposed method.

Research Area(s)

  • Deadbeat-direct torque and flux control (DB-DTFC), harmonic currents, model predictive control (MPC), multiple voltage vectors, permanent magnet (PM) machine, reference voltage vector, six-phase machine