Simplex Guided Extremum Seeking Control With Convergence Detection to Improve Global Performance

This paper presents a novel approach to improve the global performance of extremum seeking control (ESC). This algorithm employs perturbation-based ESC to find local extrema and a simplex-based algorithm to search for the global extremum. The two methods are employed in an iterative switching manner...

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Bibliographic Details
Published in:IEEE transactions on control systems technology Vol. 24; no. 4; pp. 1266 - 1278
Main Authors: Zhang, Yinghua, Rotea, Mario, Gans, Nicholas
Format: Journal Article
Language:English
Published: New York IEEE 01.07.2016
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
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ISSN:1063-6536, 1558-0865
Online Access:Get full text
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Summary:This paper presents a novel approach to improve the global performance of extremum seeking control (ESC). This algorithm employs perturbation-based ESC to find local extrema and a simplex-based algorithm to search for the global extremum. The two methods are employed in an iterative switching manner. We propose a novel frequency-domain criterion to detect when the state of a system under ESC has converged to a local optimum. Switching from ESC to the simplex method is triggered when this criterion is satisfied. We prove that this criterion will be met within finite time, under conditions on the ESC law. Simulations and experiments demonstrate and statistically prove that this algorithm outperforms ESC or simplex-based algorithms for optimizing objective functions with multiple extrema.
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ISSN:1063-6536
1558-0865
DOI:10.1109/TCST.2015.2478079