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


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
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


Other2013 1st American Control Conference, ACC 2013
Country/TerritoryUnited States
CityWashington, DC


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


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