Title :
A unifying framework for analysis and design of extremum seeking controllers
Author :
Dragan Nešić; Ying Tan;Chris Manzie;Alireza Mohammadi;Will Moase
Author_Institution :
Department of Electrical and Electronic Engineering, The University of Melbourne, Parkville 3010, Victoria, Australia
fDate :
5/1/2012 12:00:00 AM
Abstract :
We summarize a unifying design approach to continuous-time extremum seeking that was recently reported by the authors. This approach is based on a feedback control paradigm that was to the best of our knowledge explicitly summarized for the first time in this form in our recent work. This paradigm covers some existing extremum seeking schemes, provides a direct link to off-line optimization and can be used as a unifying framework for design of novel extremum seeking schemes. Moreover, we show that other extremum seeking problem formulations can be interpreted using this unifying viewpoint. We believe that this unifying view will be invaluable to systematically design and analyze extremum seeking controllers in various settings.
Keywords :
"Optimization","Algorithm design and analysis","Convergence","Heuristic algorithms","Steady-state","Vectors","Mathematical model"
Conference_Titel :
Control and Decision Conference (CCDC), 2012 24th Chinese
Print_ISBN :
978-1-4577-2073-4
Electronic_ISBN :
1948-9447
DOI :
10.1109/CCDC.2012.6244001