Skip to main content

Research Repository

Advanced Search

Multi-objective modulated Model Predictive Control for a multilevel solid state transformer

Tarisciotti, Luca; Zanchetta, Pericle; Watson, Alan James; Wheeler, Patrick; Clare, Jon C.; Bifaretti, Stefano

Authors

Luca Tarisciotti

Profile Image

ALAN WATSON ALAN.WATSON@NOTTINGHAM.AC.UK
Associate Professor

Profile Image

PATRICK WHEELER pat.wheeler@nottingham.ac.uk
Professor of Power Electronic Systems

Jon C. Clare

Stefano Bifaretti



Abstract

Finite Control Set Model Predictive Control (FCS-MPC) offers many advantages over more traditional control techniques, such as the ability to avoid cascaded control loops, easy inclusion of constraint and fast transient response of the control system. This control scheme has been recently applied to several power conversion systems, such as two, three or more level converters, Matrix converters, etc. Unfortunately, because of the lack of presence of a modulation strategy, this approach produces spread spectrum harmonics which are difficult to filter effectively. This may results in a degraded power quality when compared to more traditional control schemes. Furthermore, high switching frequencies may be needed, considering the limited number of switching states in the converter. This paper presents a novel multi-objective Modulated predictive control strategy, which preserves the desired characteristics of FCS-MPC but produces superior waveform quality. The proposed method is validated by experimental tests on a seven level Cascaded H-Bridge Back-To-Back converter and compared to a classic MPC scheme.

Citation

Tarisciotti, L., Zanchetta, P., Watson, A. J., Wheeler, P., Clare, J. C., & Bifaretti, S. (2015). Multi-objective modulated Model Predictive Control for a multilevel solid state transformer. IEEE Transactions on Industry Applications, 51(5), https://doi.org/10.1109/TIA.2015.2429113

Journal Article Type Article
Acceptance Date Apr 25, 2015
Online Publication Date May 4, 2015
Publication Date Sep 16, 2015
Deposit Date May 5, 2016
Publicly Available Date Mar 29, 2024
Journal IEEE Transactions on Industry Applications
Print ISSN 0093-9994
Electronic ISSN 0093-9994
Publisher Institute of Electrical and Electronics Engineers
Peer Reviewed Peer Reviewed
Volume 51
Issue 5
DOI https://doi.org/10.1109/TIA.2015.2429113
Public URL https://nottingham-repository.worktribe.com/output/761094
Publisher URL http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=7101248
Additional Information c2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.

Files





You might also like



Downloadable Citations