Trajectory-based proofs for sampled-data extremum seeking control
(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)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/4246759
- author
- Khong, Sei Zhen LU ; Nešić, Dragan ; Tan, Ying and Manzie, Chris
- publishing date
- 2013
- type
- Contribution to conference
- publication status
- published
- subject
- conference name
- American Control Conference, 2013
- conference location
- Washington, DC, United States
- conference dates
- 2013-06-17 - 2016-06-19
- external identifiers
-
- scopus:84883550412
- language
- English
- LU publication?
- no
- id
- 411cffec-1533-4292-b09f-87696ad5a91c (old id 4246759)
- date added to LUP
- 2016-04-04 13:31:25
- date last changed
- 2022-01-30 00:24:28
@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}},
}