State Estimation for Fractional-Order Complex Dynamical Networks with Linear Fractional Parametric Uncertainty
Author(s) -
Hongjie Li
Publication year - 2013
Publication title -
abstract and applied analysis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.228
H-Index - 56
eISSN - 1687-0409
pISSN - 1085-3375
DOI - 10.1155/2013/178718
Subject(s) - mathematics , kronecker product , estimator , parametric statistics , state (computer science) , linear matrix inequality , singular value decomposition , stability (learning theory) , fractional calculus , fractional order system , mathematical optimization , control theory (sociology) , kronecker delta , algorithm , computer science , statistics , physics , control (management) , quantum mechanics , machine learning , artificial intelligence
This paper deals with state estimation problem for a class of fractional-order complex dynamical networks with parametric uncertainty. The parametric uncertainty is assumed to be of linear fractional form. Firstly, based on the properties of Kronecker product and the stability of fractional-order system, a sufficient condition is derived for robust asymptotic stability of linear fractional-order augmented system. Secondly, state estimation problem is then studied for the same fractional-order complex networks, where the purpose is to design a state estimator to estimate the network state through available output measurement, the existence conditions of designing state estimator are derived using matrix's singular value decomposition and LMI techniques. These conditions are in the form of linear matrix inequalities which can be readily solved by applying the LMI toolbox. Finally, two numerical examples are provided to demonstrate the validity of our approach
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