A Modified Finite Control Set Model Predictive Control for 3L−NPC Grid−Connected Inverters Using Virtual Voltage Vectors

  • Jianguo LyuEmail author
  • Binghui Ma
  • Han Yan
  • Zhendong Ji
  • Jinyong Ding
Original Article


In order to improve the performance of a 3−level neutral point clamped (3L−NPC) grid−connected inverter with finite control set model predictive control (FCS−MPC), this paper proposes a modified FCS−MPC algorithm based on the rearranged control set (MFCS−MPC). By adding synthetic virtual voltage vectors to rearrange the finite control set (FCS) of the 3L−NPC inverter, the frequency spectrum of output leg voltage becomes concentrated, which is benefited for decreasing total harmonic distortion (THD) of grid currents and makes it easier to design output filters for the grid−connected inverter. Moreover, based on switching state sequences of virtual voltage vectors, the modified predictive model of the proposed method is established considering capacitor voltage difference. Besides, according to the location of the reference output voltage vector, a preselection step is incorporated into MFCS−MPC to narrow the control set for predictions, which avoids evaluating all candidate voltage vectors in the control set, and hence, the online computational burden is significantly reduced. A prototype of 3L−NPC grid−connected inverter is established to validate the proposed MFCS−MPC method and the experimental results show that this method has excellent static and dynamic performance, with a low THD for a wide range of modulation indexes.


Current distortion Finite control set model predictive control Three-level inverter Virtual voltage vector 



The research work was supported in part by The National Natural Science Foundation of China (51707097), and the Fundamental Research Funds for the Central Universities (30917011331).


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Copyright information

© The Korean Institute of Electrical Engineers 2019

Authors and Affiliations

  1. 1.School of AutomationNanjing University of Science and TechnologyNanjingChina

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