Auto-updating of sampling time redesign for system identification under parameter uncertainty

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

5 Downloads (Pure)

Abstract

In this paper, the mid-term experimental redesign of sampling strategy has been studied to improve design robustness under model uncertainties. With this method, the whole design time horizon is divided into several zones. Parameter estimation is made with the data in each zone and the updated model is used for experimental design in the next zone until the experiment is complete. A novel auto-updating strategy is developed to determine the length of each zone to assure the identifiability for parameter estimation. No pre-settings from users are required as in previous redesign algorithms. Simulation studies on an enzyme reaction system have been conducted. The results demonstrate that, compared to the conventional offline design and the standard online redesign methods, the proposed mid-term redesign with auto-updating of zones produces data that lead to more accurate parameter identification under large uncertainties.
Original languageEnglish
Title of host publication2019 25th International Conference on Automation and Computing (ICAC)
Place of PublicationPiscataway, NJ.
PublisherIEEE
Pages169-174
Number of pages6
ISBN (Print)9781861376657
DOIs
Publication statusPublished - 11 Nov 2019
Event25th IEEE International Conference on Automation and Computing - Lancaster, United Kingdom
Duration: 5 Sep 20197 Sep 2019
http://www.cacsuk.co.uk/index.php/conferences/icac

Conference

Conference25th IEEE International Conference on Automation and Computing
CountryUnited Kingdom
CityLancaster
Period5/09/197/09/19
Internet address

Keywords

  • parameter estimation
  • mid-term experimental redesign
  • model uncertainty
  • parameter identifiability
  • time sampling strategy

Fingerprint Dive into the research topics of 'Auto-updating of sampling time redesign for system identification under parameter uncertainty'. Together they form a unique fingerprint.

  • Cite this

    Wang, K., & Yue, H. (2019). Auto-updating of sampling time redesign for system identification under parameter uncertainty. In 2019 25th International Conference on Automation and Computing (ICAC) (pp. 169-174). Piscataway, NJ.: IEEE. https://doi.org/10.23919/IConAC.2019.8895129