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Comprehensive Performance Assessment of Conventional and Sequential Predictive Control for Grid-Tied NPC Inverters: A Hardware-in-the-Loop Study

Bonaldo, Jakson; Duan, Beichen; Rivera, Marco; V. Ling, K.; Fantin, Camila; Wheeler, Patrick

Comprehensive Performance Assessment of Conventional and Sequential Predictive Control for Grid-Tied NPC Inverters: A Hardware-in-the-Loop Study Thumbnail


Authors

Jakson Bonaldo

Beichen Duan

K. V. Ling

Camila Fantin



Abstract

Model Predictive Control (MPC) has become very attractive for the efficient control of power converters. This paper compares Classical MPC (C-MPC) and Sequential MPC (S-MPC) for a three-level NPC converter. Although C-MPC is simple to implement, it faces challenges such as switching frequency variations and complex weighting factor tuning. S-MPC addresses these issues by prioritizing control objectives sequentially, eliminating weighting factors, and simplifying controller design. Simulation results show that S-MPC improves the tracking of output currents, reduces harmonic distortion, and enhances the balancing of dc–link voltages under steady-state and transient conditions. These findings establish S-MPC as a robust alternative to C-MPC, improving power quality and system performance in multilevel converter applications.

Citation

Bonaldo, J., Duan, B., Rivera, M., V. Ling, K., Fantin, C., & Wheeler, P. (2025). Comprehensive Performance Assessment of Conventional and Sequential Predictive Control for Grid-Tied NPC Inverters: A Hardware-in-the-Loop Study. Energies, 18(12), Article 3132. https://doi.org/10.3390/en18123132

Journal Article Type Article
Acceptance Date Jun 12, 2025
Online Publication Date Jun 14, 2025
Publication Date Jun 2, 2025
Deposit Date Jul 10, 2025
Publicly Available Date Jul 10, 2025
Journal Energies
Electronic ISSN 1996-1073
Publisher MDPI
Peer Reviewed Peer Reviewed
Volume 18
Issue 12
Article Number 3132
DOI https://doi.org/10.3390/en18123132
Keywords grid-connected inverter; neutral-point clamped converter (NPC); power quality; renewable energy sources; sequential model predictive control
Public URL https://nottingham-repository.worktribe.com/output/50704886
Publisher URL https://www.mdpi.com/1996-1073/18/12/3132

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