Improved Indirect Model Predictive Control for Enhancing Dynamic Performance of Modular Multilevel Converter

Model predictive control has become a tremendously popular control method for power converters, notably a modular multilevel converter, owing to the ability to control various objectives at once with a particular cost function and prominent dynamic performance. However, the high number of submodules...

Full description

Saved in:
Bibliographic Details
Published in:Electronics (Basel) 2020-09, Vol.9 (9), p.1405
Main Authors: Nguyen, Minh Hoang, Kwak, Sangshin
Format: Article
Language:English
Subjects:
Computing time
Cost function
Methods
Multilevel
Power converters
Predictive control
Stability
Steady state
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Model predictive control has become a tremendously popular control method for power converters, notably a modular multilevel converter, owing to the ability to control various objectives at once with a particular cost function and prominent dynamic performance. However, the high number of submodules in cascaded control means that the model predictive control for the modular multilevel converter suffers from a computational burden. Several approaches focused on reducing the computational burden based on limiting the number of possible switching states (possible choices) to be evaluated at each sampling instant. The dynamic performance of the modular multilevel converter is degraded in a transient state, despite the reduced computational burden. This paper presents an improved indirect model predictive control method to reduce the computational burden and enhance the dynamic performance. The proposed approach considers the steady-state and transient state individually and applies a different range of choices for each specific case. The range of choices during the steady-state is limited in order to reduce the computational burden without deteriorating the output quality, whereas the number of choices will be increased during the transient state to guarantee dynamic performance. The results that were obtained by implementing an experiment on a laboratory setup of a single-phase modular multilevel converter are presented in order to verify the proposed approach’s effectiveness. From the experimental setup, the computational time in the proposed approach was reduced by about 75% when compared with the conventional indirect model predictive control, whereas keeping fast dynamic performance.
ISSN:2079-9292
2079-9292
DOI:10.3390/electronics9091405