A distributed model predictive control strategy for back-to-back converters

Tarisciotti, Luca; Lo Calzo, Giovanni; Gaeta, Alberto; Zanchetta, Pericle; Valencia, Felipe; Saez, Doris

Abstract

In recent years Model Predictive Control (MPC) has been successfully used for the control of power electronics converters with different topologies and for different applications. 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. On the other hand, the controller computational burden increases exponentially with the system complexity and may result in an unfeasible realization on modern digital control boards. This paper proposes a novel Distributed Model Predictive Control, which is able to achieve the same performance of the classical Model Predictive Control whilst reducing the computational requirements of its implementation. The proposed control approach is tested on a AC/AC converter in a back-to-back configuration used for power flow management. Simulation results are provided and validated through experimental testing in several operating conditions.

Citation

Tarisciotti, L., Lo Calzo, G., Gaeta, A., Zanchetta, P., Valencia, F., & Saez, D. (2016). A distributed model predictive control strategy for back-to-back converters. IEEE Transactions on Industrial Electronics, 63(9), 5867-5878. https://doi.org/10.1109/TIE.2016.2527693

• Journal Article Type: Article
• Acceptance Date: Jan 13, 2016
• Publication Date: Feb 11, 2016
• Deposit Date: Aug 3, 2016
• Publicly Available Date: Aug 3, 2016
• Journal: IEEE Transactions on Industrial Electronics
• Print ISSN: 0278-0046
• Electronic ISSN: 1557-9948
• Publisher: Institute of Electrical and Electronics Engineers
• Peer Reviewed: Peer Reviewed
• Volume: 63
• Issue: 9
• Pages: 5867-5878
• DOI: https://doi.org/10.1109/TIE.2016.2527693
• Keywords: Predictive control, Nonlinear control systems,; Back-to-back converters
• Public URL: https://nottingham-repository.worktribe.com/output/772939
• Publisher URL: http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=7403993
• Additional Information: © 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, 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 component of this work in other works.
• Contract Date: Aug 3, 2016