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Adaptive sliding mode observation in a network of dynamical systems
Author(s) -
Me Prathyush P.,
Edwards Christopher,
Shtessel Yuri B.
Publication year - 2016
Publication title -
international journal of adaptive control and signal processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.73
H-Index - 66
eISSN - 1099-1115
pISSN - 0890-6327
DOI - 10.1002/acs.2670
Subject(s) - control theory (sociology) , observer (physics) , linear matrix inequality , mode (computer interface) , bounded function , state observer , computer science , state (computer science) , process (computing) , complex network , node (physics) , mathematics , nonlinear system , mathematical optimization , engineering , algorithm , control (management) , artificial intelligence , physics , mathematical analysis , structural engineering , quantum mechanics , world wide web , operating system
Summary This paper considers the problem of reconstructing state information in all the nodes of a complex network of dynamical systems. The individual nodes comprise a known linear part and unknown but bounded uncertainties in certain channels of the system. A supervisory adaptive sliding mode observer configuration is proposed for estimating the states. A linear matrix inequality (LMI) approach is suggested to synthesise the gains of the sliding mode observer. Although deployed centrally to estimate all the states of the complex network, the design process depends only on the dynamics of an individual node of the network. The methodology is demonstrated by considering a network of Chua oscillators. Copyright © 2016 John Wiley & Sons, Ltd.