A Comprehensive Study of Sequential Model Predictive Control Methods for Multilevel Inverters

Due to the low computational burden, sequential model predictive control (SMPC) methods have emerged as promising solutions for multilevel inverters (MLIs). Over the years, several SMPC approaches focusing on either load current or load voltage as the primary objective have been explored for MLIs. These methods have adopted philosophies such as cost function with weighting factors, offline switching vector selection or inherent strategies to minimize common-mode voltage (CMV). However, the literature lacks a comprehensive analysis of SMPC methods with CMV minimization and their pros and cons on system performance. To fill the research gap, this paper presents the philosophies behind various SMPC methods for four-level inverters (FLIs), along with the mathematical models utilized in SMPC implementation and case studies to highlight their performances. Finally, a comparative analysis of SMPC methods is provided, aiding researchers in selecting suitable methods for their applications.