Model predictive control of hot-rolled strip cooling process using variable-resolution model

Kentaro Hirata, Daijiro Udagawa, Yoichiro Masui, Yukinori Nakamura

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

1 Citation (Scopus)

Abstract

Model Predictive Control is an effective control method for nonlinear plants with constraints. However, application to large-scale systems and/or processes that require high sampling rate is quite challenging because of the heavy computation. Here we consider MPC approach for the cooling process of hot-rolled strip having 3D thermal distribution. To solve this large-scale problem, we propose a method to change the resolution of the model dynamically according to the uniformity of the thermal distributions in the directions of interest. Combined with a hierarchical control strategy to flatten the thermal distribution in a certain direction, one can balance the computational load across the cooling process.

Original languageEnglish
Title of host publicationProceedings of the IECON 2016 - 42nd Annual Conference of the Industrial Electronics Society
PublisherIEEE Computer Society
Pages215-222
Number of pages8
ISBN (Electronic)9781509034741
DOIs
Publication statusPublished - Dec 21 2016
Event42nd Conference of the Industrial Electronics Society, IECON 2016 - Florence, Italy
Duration: Oct 24 2016Oct 27 2016

Publication series

NameIECON Proceedings (Industrial Electronics Conference)

Other

Other42nd Conference of the Industrial Electronics Society, IECON 2016
CountryItaly
CityFlorence
Period10/24/1610/27/16

Keywords

  • Model Predictive Control
  • Multi Resolution
  • Process Modeling

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Electrical and Electronic Engineering

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