Improved ROGI-FLL-Based Sensorless Model Predictive Current Control With MRAS Parameter Identification for SPMSM Drives

Yao, Xuliang; Huang, Shengqi; Wang, Jingfang; Ma, He; Zhang, Guowang; Wang, Yujian

doi:10.1109/jestpe.2022.3230700

Cited by 6 publications

(1 citation statement)

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“…Time-varying changes in electrical (resistances, inductances, and flux linkage of permanent magnets) and mechanical (inertia and viscous friction) parameters are inevitable. To deal with the parameter dependency problem, incremental model-based MPCs [10]- [12], model-free MPCs [13]- [15], disturbance observer-based MPCs [16]- [18], and MPCs combined with parameter estimation [19] have been proposed. MPC strategies directly control the switching states of power converters but the availability of the switching combinations for a power converter is limited, resulting in high current/torque harmonics in electric drives.…”

Section: Introductionmentioning

confidence: 99%

A Review on Weighting Factor Design of Finite Control Set Model Predictive Control Strategies for AC Electric Drives

Zerdali,

Rivera,

Wheeler

2024

IEEE Trans. Power Electron.

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Model predictive control (MPC) has been widely applied to AC electric drives over the last decade. Despite extreme efforts and proposed effective solutions, the researchers are still seeking to find more effective solutions for weighting factor (WF) design, parameter dependency, current/torque harmonics, variable switching frequency, and computational complexity. This paper presents a review of the WF design techniques of MPC strategies for AC electric drives. Thus, it aims to inform readers about the proposed techniques for WF design of MPC strategies and to accelerate their future research in this promising area.

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