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Unified frameworks for sampled-data extremum seeking control: Global optimisation and multi-unit systems

Khong, Sei Zhen LU ; Nešić, Dragan; Tan, Ying and Manzie, Chris (2013) In Automatica
Abstract
Two frameworks are proposed for extremum seeking of general nonlinear plants based on a sampled-data control law, within which a broad class of nonlinear programming methods is accommodated. It is established that under some generic assumptions, semi-global practical convergence to a global extremum can be achieved. In the case where the extremum seeking algorithm satisfies a stronger asymptotic stability property, the converging sequence is also shown to be stable using a trajectory-based proof, as opposed to a Lyapunov-function-type approach. The former is more straightforward and insightful. This allows for more general optimisation algorithms than considered in existing literature, such as those which do not admit a state-update... (More)
Two frameworks are proposed for extremum seeking of general nonlinear plants based on a sampled-data control law, within which a broad class of nonlinear programming methods is accommodated. It is established that under some generic assumptions, semi-global practical convergence to a global extremum can be achieved. In the case where the extremum seeking algorithm satisfies a stronger asymptotic stability property, the converging sequence is also shown to be stable using a trajectory-based proof, as opposed to a Lyapunov-function-type approach. The former is more straightforward and insightful. This allows for more general optimisation algorithms than considered in existing literature, such as those which do not admit a state-update realisation and/or Lyapunov functions. Lying at the heart of the analysis throughout is robustness of the optimisation algorithms to additive perturbations of the objective function. Multi-unit extremum seeking is also investigated with the objective of accelerating the speed of convergence. (Less)
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author
publishing date
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Contribution to journal
publication status
published
subject
in
Automatica
publisher
Pergamon
external identifiers
  • Scopus:84881479515
ISSN
0005-1098
language
English
LU publication?
no
id
ddff399a-230b-4992-a281-dddcd30f663c (old id 4246747)
date added to LUP
2014-01-20 11:20:46
date last changed
2016-11-27 04:38:28
@misc{ddff399a-230b-4992-a281-dddcd30f663c,
  abstract     = {Two frameworks are proposed for extremum seeking of general nonlinear plants based on a sampled-data control law, within which a broad class of nonlinear programming methods is accommodated. It is established that under some generic assumptions, semi-global practical convergence to a global extremum can be achieved. In the case where the extremum seeking algorithm satisfies a stronger asymptotic stability property, the converging sequence is also shown to be stable using a trajectory-based proof, as opposed to a Lyapunov-function-type approach. The former is more straightforward and insightful. This allows for more general optimisation algorithms than considered in existing literature, such as those which do not admit a state-update realisation and/or Lyapunov functions. Lying at the heart of the analysis throughout is robustness of the optimisation algorithms to additive perturbations of the objective function. Multi-unit extremum seeking is also investigated with the objective of accelerating the speed of convergence.},
  author       = {Khong, Sei Zhen and Nešić, Dragan and Tan, Ying and Manzie, Chris},
  issn         = {0005-1098},
  language     = {eng},
  publisher    = {ARRAY(0x93b73f8)},
  series       = {Automatica},
  title        = {Unified frameworks for sampled-data extremum seeking control: Global optimisation and multi-unit systems},
  year         = {2013},
}