Journal article

Fast extremum seeking on Hammerstein plants: A model-based approach

J Sharafi, WH Moase, C Manzie

Automatica | Elsevier | Published : 2015

Abstract

Abstract Partial plant knowledge may be used to develop model-based extremum seekers; however, existing results rely on a type of time-scale separation which leads to slow optimization relative to the plant dynamics. In this work, a fast model-based extremum seeking scheme is proposed for a Hammerstein plant, and semi-global stability results are provided. The structure of a Hammerstein plant is used to advantage in designing filters that enable the extremum seeker to act on a faster time-scale than the plant dynamics. This leads to fast convergence while maintaining semi-global stability.

University of Melbourne Researchers

Grants

Awarded by Ford Motor Company of Australia


Funding Acknowledgements

This work was supported under the Australian Research Council's Discovery Projects funding scheme (Project DP120101830). The material in this paper was presented at the 52nd IEEE Conference on Decision and Control, December 10-13, 2013, Florence, Italy. This paper was recommended for publication in revised form by Associate Editor Raul Ordonez under the direction of Editor Miroslav Krstic.