Extremum seeking control with data-based disturbance feedforward

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

6 Citations (Scopus)
5 Downloads (Pure)

Abstract

This paper presents a practical extension to the classical gradient-based extremum seeking control for the case when the disturbances responsible for the changes in the extremum of a related performance function can be measured. The additional information is used to improve accuracy, convergence speed and robustness of the underlying ESC scheme. Based on the disturbance measurements a map between them and the optimal inputs is iteratively constructed and used as an extremum seeking feedforward. A supervising state-machine is designed to regulate feedforward and search processes ensuring the latter is conducted in the close vicinity of an extremum. The search is based on the sinusoidal input perturbation introduced each time the disturbance is detected and removed once the optimal set-point is identified. Simulation results for the cases of photovoltaic and turbine driven electrical generator systems demonstrate the benefits of the presented design.

Original languageEnglish
Title of host publicationProceedings of the American Control Conference, 4-6 June 2014, Portland, Oregon
Place of PublicationPiscataway
PublisherInstitute of Electrical and Electronics Engineers
Pages3627-3632
Number of pages6
ISBN (Print)9781479932726
DOIs
Publication statusPublished - 2014
Event2014 American Control Conference (ACC 2014), June 4-6, 2014, Portland, OR, USA - Hilton Portland & Executive Tower , Portland, OR, United States
Duration: 4 Jun 20146 Jun 2014
http://acc2014.a2c2.org/

Conference

Conference2014 American Control Conference (ACC 2014), June 4-6, 2014, Portland, OR, USA
Abbreviated titleACC 2014
CountryUnited States
CityPortland, OR
Period4/06/146/06/14
Internet address

Keywords

  • Control applications
  • Estimation
  • Optimization algorithms

Fingerprint Dive into the research topics of 'Extremum seeking control with data-based disturbance feedforward'. Together they form a unique fingerprint.

  • Cite this

    Marinkov, S., de Jager, B., & Steinbuch, M. (2014). Extremum seeking control with data-based disturbance feedforward. In Proceedings of the American Control Conference, 4-6 June 2014, Portland, Oregon (pp. 3627-3632). Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/ACC.2014.6858832