Author
Listed:
- Jakson Bonaldo
(Department of Electrical Engineering, Federal University of Mato Grosso, Avenida Fernando Correa da Costa, 1367, Cuiaba 78060-900, Brazil)
- Beichen Duan
(School of Electrical & Electronics Engineering, Nanyang Technological University (NTU), Singapore 637331, Singapore)
- Marco Rivera
(Department of Electrical and Electronic Engineering, Faculty of Engineering, Power Electronics, Machines and Control (PEMC) Research Institute, University of Nottingham, 15 Triumph Rd, Lenton, Nottingham NG7 2GT, UK
Laboratorio de Conversión de Energías y Electrónica de Potencia (LCEEP), Vicerrectoría Académica, Universidad de Talca, 2 Norte # 685, Talca 3460000, Chile)
- K. V. Ling
(School of Electrical & Electronics Engineering, Nanyang Technological University (NTU), Singapore 637331, Singapore)
- Camila Fantin
(Department of Electrical Engineering, Federal University of Mato Grosso, Avenida Fernando Correa da Costa, 1367, Cuiaba 78060-900, Brazil)
- Patrick Wheeler
(Department of Electrical and Electronic Engineering, Faculty of Engineering, Power Electronics, Machines and Control (PEMC) Research Institute, University of Nottingham, 15 Triumph Rd, Lenton, Nottingham NG7 2GT, UK)
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.
Suggested Citation
Jakson Bonaldo & Beichen Duan & Marco Rivera & K. V. Ling & Camila Fantin & Patrick Wheeler, 2025.
"Comprehensive Performance Assessment of Conventional and Sequential Predictive Control for Grid-Tied NPC Inverters: A Hardware-in-the-Loop Study,"
Energies, MDPI, vol. 18(12), pages 1-23, June.
Handle:
RePEc:gam:jeners:v:18:y:2025:i:12:p:3132-:d:1679044
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