Modulated model predictive control for a 7-level cascaded h-bridge back-to-back converter

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

Abstract

Multilevel Converters are known to have many advantages for electricity network applications. In particular Cascaded H-Bridge Converters are attractive because of their inherent modularity and scalability. Predictive control for power converters is advantageous as a result of its applicability to discrete system and fast response. In this paper a novel control technique, named Modulated Model Predictive Control, is introduced with the aim to increase the performance of Model Predictive Control. The proposed controller address a modulation scheme as part of the minimization process. The proposed control technique is described in detail, validated through simulation and experimental testing and compared with Dead-Beat and traditional Model Predictive Control. The results show the increased performance of the Modulated Model Predictive Control with respect to the classic Finite Control Set Model Predictive Control, in terms ofcurrent waveform THD. Moreover the proposed controller allows a multi-objective control, with respect to Dead-Beat Control that does not present this capability.

Citation

Tarisciotti, L., Zanchetta, P., Watson, A. J., Bifaretti, S., & Clare, J. C. (2014). Modulated model predictive control for a 7-level cascaded h-bridge back-to-back converter. IEEE Transactions on Industrial Electronics, 61(10), https://doi.org/10.1109/TIE.2014.2300056

• Journal Article Type: Article
• Acceptance Date: Nov 20, 2012
• Publication Date: Jan 14, 2014
• Deposit Date: Jul 8, 2016
• Publicly Available Date: Oct 14, 2016
• Journal: IEEE Transactions on Industrial Electronics
• Print ISSN: 0278-0046
• Publisher: Institute of Electrical and Electronics Engineers
• Peer Reviewed: Peer Reviewed
• Volume: 61
• Issue: 10
• DOI: https://doi.org/10.1109/TIE.2014.2300056
• Keywords: Multilevel Converters; Predictive Control; Smart Grid
• Public URL: https://nottingham-repository.worktribe.com/output/721811
• Publisher URL: http://ieeexplore.ieee.org/document/6712126/
• Additional Information: (c)2014 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.