Data-driven control of infinite dimensional systems: Application to a continuous crystallizer

Pauline Kergus

Research output: Contribution to journalArticlepeer-review

Abstract

Controlling infinite dimensional models remains a challenging task for many practitioners since they are not suitable for traditional control design techniques or will result in a high-order controller too complex for implementation. Therefore, the model or the controller need to be reduced to an acceptable dimension, which is time-consuming, requires some expertise and may introduce numerical error. This paper tackles the control of such a system, namely a continuous crystallizer, and compares two different data-driven strategies: the first one is a structured robust technique while the other one, called L-DDC, is based on the Loewner interpolatory framework.

Original languageEnglish
Pages (from-to)2120-2125
Number of pages6
JournalIEEE Control Systems Letters
Volume5
Issue number6
DOIs
Publication statusPublished - 2021 Dec 1

Subject classification (UKÄ)

  • Control Engineering

Free keywords

  • Control applications.
  • Crystallizers
  • Crystals
  • Frequency response
  • Model/Controller reduction
  • Process control
  • Resonant frequency
  • Robust control
  • Stability of linear systems
  • Steady-state

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