Extremum seeking control with data-based disturbance feedforward

Sava Marinkov, Bram de Jager, Maarten Steinbuch

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

10 Citations (Scopus)
5 Downloads (Pure)


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
Number of pages6
ISBN (Print)9781479932726
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


Conference2014 American Control Conference (ACC 2014), June 4-6, 2014, Portland, OR, USA
Abbreviated titleACC 2014
Country/TerritoryUnited States
CityPortland, OR
Internet address


  • Control applications
  • Estimation
  • Optimization algorithms


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