A Review on Weighting Factor Design of Finite Control Set Model Predictive Control Strategies for AC Electric Drives
Emrah Zerdali, Marco Rivera, Patrick Wheeler
Abstract
Model predictive control has been widely applied to AC electric drives over the last decade. Despite the proposed solutions, researchers are still seeking to find more effective solutions for weighting factor design, parameter dependency, current/torque harmonics, variable switching frequency, and computational complexity. This paper presents a comprehensive review of the weighting factor design techniques for finite control set model predictive control strategies for AC electric drives. First, the paper introduces the conventional model predictive control techniques for electric drives over permanent magnet synchronous motors. Second, weighting factor design methods are discussed under two main headings: weighting factor selection and weighting factor elimination methods. Third, the ongoing challenges and future trends are addressed by considering the current literature. Based on this review, it is obvious that each weighting factor design method still has problems that await more effective solutions. Finally, this paper reviews various weighting factor design methods for AC electric drives, reveals the advantages and disadvantages of existing methods in terms of control performance, flexibility, design complexity, and computational complexity, and highlights future trends.