Trajectory-based proofs for sampled-data extremum seeking control

Sei Zhen Khong, Dragan Nesic, Ying Tan, Chris Manzie

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

1 Scopus citations

Abstract

Extremum seeking of nonlinear systems based on a sampled-data control law is revisited. It is established that under some generic assumptions, semi-global practical asymptotically stable convergence to an extremum can be achieved. To this end, trajectory-based arguments are employed, by contrast with Lyapunov-function-type approaches in the existing literature. The proof is simpler and more straightforward; it is based on assumptions that are in general easier to verify. The proposed extremum seeking framework may encompass more general optimisation algorithms, such as those which do not admit a state-update realisation and/or Lyapunov functions. Multi-unit extremum seeking is also investigated within the context of accelerating the speed of convergence.

Original languageEnglish (US)
Title of host publication2013 American Control Conference, ACC 2013
Pages2751-2756
Number of pages6
StatePublished - Sep 11 2013
Event2013 1st American Control Conference, ACC 2013 - Washington, DC, United States
Duration: Jun 17 2013Jun 19 2013

Publication series

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

Other

Other2013 1st American Control Conference, ACC 2013
Country/TerritoryUnited States
CityWashington, DC
Period6/17/136/19/13

Keywords

  • Extremum seeking
  • multi-unit systems
  • robustness
  • sampled-data control
  • trajectory properties

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