Result: Extremum seeking under stochastic noise and applications to mobile sensors
Title:
Extremum seeking under stochastic noise and applications to mobile sensors
Authors:
Source:
Automatica (Oxford). 46(8):1243-1251
Publisher Information:
Kidlington: Elsevier, 2010.
Publication Year:
2010
Physical Description:
print, 1/4 p
Original Material:
INIST-CNRS
Subject Terms:
Control theory, operational research, Automatique, recherche opérationnelle, Computer science, Informatique, Sciences exactes et technologie, Exact sciences and technology, Sciences appliquees, Applied sciences, Informatique; automatique theorique; systemes, Computer science; control theory; systems, Automatique théorique. Systèmes, Control theory. Systems, Algorithme récursif, Recursive algorithm, Algoritmo recursivo, Approche probabiliste, Probabilistic approach, Enfoque probabilista, Capteur mesure, Measurement sensor, Captador medida, Localisation source, Source localization, Localización fuente, Rapport signal bruit, Signal to noise ratio, Relación señal ruido, Recherche extrémale, Extreme search, Investigación extremal, Source bruit, Noise source, Fuente ruido, Système paramètre variable, Time varying system, Sistema parámetro variable, Convergence, Extremum seeking, Mobile sensors, Noise source localization, Stochastic recursive algorithms
Document Type:
Academic journal
Article
File Description:
text
Language:
English
Author Affiliations:
ACCESS Linnaeus Center, School of Electrical Engineering, Royal Institute of Technology, 100 44 Stockholm, Sweden
Department of Industrial and Enterprise Systems Engineering and the Coordinated Science Laboratory, University of Illinois, Urbana-Champaign, IL, United States
Department of Industrial and Enterprise Systems Engineering and the Coordinated Science Laboratory, University of Illinois, Urbana-Champaign, IL, United States
ISSN:
0005-1098
Rights:
Copyright 2015 INIST-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
Notes:
Computer science; theoretical automation; systems
Accession Number:
edscal.23072126
Database:
PASCAL Archive
Further Information
In this paper the extremum seeking algorithm with sinusoidal perturbations has been extended and modified in two ways: (a) the output of the system is corrupted with measurement noise; (b) the amplitudes of the perturbation signals, as well as the gain of the integrator block, are time varying and tend to zero at a pre-specified rate. Convergence to the extremal point, with probability one, has been proved. Also, as a consequence of being able to cope with a stochastic environment, it has been shown how the proposed algorithm can be applied to mobile sensors as a tool for achieving the optimal observation positions. The proposed algorithm has been illustrated through several simulations.