Closed-loop system identification of restricted complexity models using iterative refinement

Daniel Rivera, Saurabh Bhatnagar

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

6 Scopus citations

Abstract

A novel technique for identifying reduced-order models in the closed-loop is presented. The method arrives at a process model and its corresponding compensator in an iterative fashion by introducing a series of step changes at the manipulated variable. The bias introduced into the identification data set by the closed-loop system, coupled with a control-relevant prefilter, yields a model whose corresponding control system improves its performance at every step. The method is appealing to chemical engineering practitioners because it combines the tasks of system identification with controller commissioning to produce a simple-to-use yet reliable autotuning procedure.

Original languageEnglish (US)
Title of host publicationAmerican Control Conference
PublisherPubl by IEEE
Pages1993-1994
Number of pages2
ISBN (Print)0780308611, 9780780308619
DOIs
StatePublished - 1993
EventProceedings of the 1993 American Control Conference Part 3 (of 3) - San Francisco, CA, USA
Duration: Jun 2 1993Jun 4 1993

Publication series

NameAmerican Control Conference

Other

OtherProceedings of the 1993 American Control Conference Part 3 (of 3)
CitySan Francisco, CA, USA
Period6/2/936/4/93

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

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    Rivera, D., & Bhatnagar, S. (1993). Closed-loop system identification of restricted complexity models using iterative refinement. In American Control Conference (pp. 1993-1994). (American Control Conference). Publ by IEEE. https://doi.org/10.23919/acc.1993.4793226