Long-Prediction-Horizon Near-Optimal Model Predictive Grid Current Control for PWM-Driven VSIs with LCL Filters

Chee Shen Lim*, Hui Hwang Goh, Sze Sing Lee

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

13 Citations (Scopus)


This article proposed and investigated a near-optimal finite-control-set model-predictive grid current control (NOP-MPGCC) for voltage source inverters (VSIs) with actively damped LCL filters. It carries three advantages: (i) the constant-frequency pulsewidth modulator produces regular switching spectrum - which can ease the LCL filter design process in grid current control applications with medium-to-high carrier ratio; (ii) it avoids the use of the usual first-order assumption in most PI-/PR-based control and the common simplifications adopted in some existing FCS-MPC schemes. This is achieved by considering the third-order behavior using long prediction horizon; and (iii) it can operate near and across the critical frequency, defined using the established classical control definition. Moreover, it retains the intuitive enumeration structure and maximizes the dc-bus utilization through the consideration of entire hexagonal vector space at every control cycle. The theoretical derivation, simulation, and experiment results verify that NOP-MPGCC is potentially a viable direct grid current control scheme for PWM-VSIs with actively damped LCL filters.

Original languageEnglish
Article number9146179
Pages (from-to)2246-2257
Number of pages12
JournalIEEE Transactions on Power Electronics
Issue number2
Publication statusPublished - Feb 2021
Externally publishedYes


  • Cost function
  • grid current
  • model predictive control (MPC)
  • near-optimal MPC
  • optimal control


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