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

Research output: Chapter in Book/Report/Conference proceedingPaper in conference proceedingpeer-review


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. Model/Controller reduction, Stability of linear systems, Control applications.

Original languageEnglish
Title of host publication2021 American Control Conference, ACC 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages6
ISBN (Electronic)9781665441971
Publication statusPublished - 2021 May 25
Event2021 American Control Conference, ACC 2021 - Virtual, New Orleans, United States
Duration: 2021 May 252021 May 28

Publication series

NameProceedings of the American Control Conference
ISSN (Print)0743-1619


Conference2021 American Control Conference, ACC 2021
Country/TerritoryUnited States
CityVirtual, New Orleans

Subject classification (UKÄ)

  • Control Engineering


Dive into the research topics of 'Data-driven control of infinite dimensional systems: Application to a continuous crystallizer'. Together they form a unique fingerprint.

Cite this