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Trajectory-based proofs for sampled-data extremum seeking control

Khong, Sei Zhen LU ; Nešić, Dragan; Tan, Ying and Manzie, Chris (2013) American Control Conference, 2013
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... (More)
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. (Less)
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Contribution to conference
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published
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conference name
American Control Conference, 2013
external identifiers
  • Scopus:84883550412
language
English
LU publication?
no
id
411cffec-1533-4292-b09f-87696ad5a91c (old id 4246759)
date added to LUP
2014-02-14 12:46:31
date last changed
2017-01-01 08:12:31
@misc{411cffec-1533-4292-b09f-87696ad5a91c,
  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.},
  author       = {Khong, Sei Zhen and Nešić, Dragan and Tan, Ying and Manzie, Chris},
  language     = {eng},
  title        = {Trajectory-based proofs for sampled-data extremum seeking control},
  year         = {2013},
}