Auto-tuning the cost function weight factors in a model predictive controller for a matrix converter VAR compensator

Mohammad B. Shadmand, Robert Balog, Haitham Abu-Rub

Research output: Chapter in Book/Report/Conference proceedingConference contribution

10 Citations (Scopus)

Abstract

This paper presents an auto-tuning technique for online selection of the cost function weight factors in model predictive control (MPC). The weight factors in the cost function with multiple control objectives directly affect the performance and robustness of the MPC. The proposed method in this paper determines the optimum weight factors of the cost function for each sampling time; the optimization of the weight factors is done based on the prediction of the absolute error of the optimization objective and the corresponding constraints. The application considered is a reactive power compensation technique using MPC of a direct matrix converter. This technique compensates lagging power factor loads using inductive energy storage elements instead of electrolytic capacitors (e-caps). The result demonstrates that the proposed auto-tuning approach of cost function weights makes the control algorithm robust to parameter variation and other uncertainties such as load variation. The proposed capacitor-less reactive power compensator based on auto tuned MPC cost function weight factor is implemented experimentally using dSpace DS1007.

Original languageEnglish
Title of host publication2015 IEEE Energy Conversion Congress and Exposition, ECCE 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages3807-3814
Number of pages8
ISBN (Electronic)9781467371506
DOIs
Publication statusPublished - 27 Oct 2015
Event7th Annual IEEE Energy Conversion Congress and Exposition, ECCE 2015 - Montreal, Canada
Duration: 20 Sep 201524 Sep 2015

Other

Other7th Annual IEEE Energy Conversion Congress and Exposition, ECCE 2015
CountryCanada
CityMontreal
Period20/9/1524/9/15

Fingerprint

Cost functions
Model predictive control
Tuning
Controllers
Reactive power
Electrolytic capacitors
Robustness (control systems)
Energy storage
Capacitors
Matrix converters
Sampling

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering

Cite this

Shadmand, M. B., Balog, R., & Abu-Rub, H. (2015). Auto-tuning the cost function weight factors in a model predictive controller for a matrix converter VAR compensator. In 2015 IEEE Energy Conversion Congress and Exposition, ECCE 2015 (pp. 3807-3814). [7310198] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ECCE.2015.7310198

Auto-tuning the cost function weight factors in a model predictive controller for a matrix converter VAR compensator. / Shadmand, Mohammad B.; Balog, Robert; Abu-Rub, Haitham.

2015 IEEE Energy Conversion Congress and Exposition, ECCE 2015. Institute of Electrical and Electronics Engineers Inc., 2015. p. 3807-3814 7310198.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Shadmand, MB, Balog, R & Abu-Rub, H 2015, Auto-tuning the cost function weight factors in a model predictive controller for a matrix converter VAR compensator. in 2015 IEEE Energy Conversion Congress and Exposition, ECCE 2015., 7310198, Institute of Electrical and Electronics Engineers Inc., pp. 3807-3814, 7th Annual IEEE Energy Conversion Congress and Exposition, ECCE 2015, Montreal, Canada, 20/9/15. https://doi.org/10.1109/ECCE.2015.7310198
Shadmand MB, Balog R, Abu-Rub H. Auto-tuning the cost function weight factors in a model predictive controller for a matrix converter VAR compensator. In 2015 IEEE Energy Conversion Congress and Exposition, ECCE 2015. Institute of Electrical and Electronics Engineers Inc. 2015. p. 3807-3814. 7310198 https://doi.org/10.1109/ECCE.2015.7310198
Shadmand, Mohammad B. ; Balog, Robert ; Abu-Rub, Haitham. / Auto-tuning the cost function weight factors in a model predictive controller for a matrix converter VAR compensator. 2015 IEEE Energy Conversion Congress and Exposition, ECCE 2015. Institute of Electrical and Electronics Engineers Inc., 2015. pp. 3807-3814
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