Feedback control of linear distributed parameter systems via adaptive model reduction in the presence of device network communication constraints

Davood Babaei Pourkargar, Antonios Armaou

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

8 Scopus citations

Abstract

We focus on model-based networked control of general linear dissipative distributed parameter systems, the infinite dimensional representation of which can be decomposed to finite-dimensional slow and infinite-dimensional fast and stable subsystems. The controller synthesis of such systems is addressed using adaptive proper orthogonal decomposition (APOD). Specifically, APOD is used to recursively construct locally accurate low dimensional reduced order models (ROMs). The ROM is included in the control structure to reduce the frequency of spatially distributed sensor measurements over the network by suspending communication. The main objective of the current work is to identify a criterion for minimizing communication bandwidth (snapshots transfer rate) from the distributed sensors to the control structure considering closed-loop stability. The proposed approach is successfully used to regulate the thermal dynamics in a tubular chemical reactor.

Original languageEnglish (US)
Title of host publication2014 American Control Conference, ACC 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1667-1673
Number of pages7
ISBN (Print)9781479932726
DOIs
StatePublished - 2014
Event2014 American Control Conference, ACC 2014 - Portland, OR, United States
Duration: Jun 4 2014Jun 6 2014

Publication series

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

Other

Other2014 American Control Conference, ACC 2014
Country/TerritoryUnited States
CityPortland, OR
Period6/4/146/6/14

Keywords

  • Distributed parameter systems
  • Process control
  • Reduced order modeling

Fingerprint

Dive into the research topics of 'Feedback control of linear distributed parameter systems via adaptive model reduction in the presence of device network communication constraints'. Together they form a unique fingerprint.

Cite this