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System identification by operatorial cancellation of nonlinear terms and application to a class of Volterra models
Author(s) -
Casenave C.,
Montseny E.,
Montseny G.
Publication year - 2016
Publication title -
international journal of robust and nonlinear control
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.361
H-Index - 106
eISSN - 1099-1239
pISSN - 1049-8923
DOI - 10.1002/rnc.3622
Subject(s) - nonlinear system , identification (biology) , term (time) , nonlinear system identification , class (philosophy) , component (thermodynamics) , computer science , a priori and a posteriori , scope (computer science) , linear model , system identification , mathematics , control theory (sociology) , mathematical optimization , artificial intelligence , machine learning , data mining , measure (data warehouse) , control (management) , physics , epistemology , quantum mechanics , biology , programming language , thermodynamics , philosophy , botany
Summary In this paper, a method is proposed for the identification of some SISO nonlinear models with two ill‐known components of different nature: a linear (possibly dynamic) part and a static nonlinear one. This method is well adapted when no a priori information is available about the nonlinear component to be identified. It is based on a difference operator, which enables to cancel the nonlinear term when applied to the model. Only the ill‐known linear part remains in the transformed model; it can therefore be identified independently of the nonlinear term. Based on the identified linear component, we have access to a pseudograph of the nonlinear term, whose shape can give precious information for the parameterization of the unknown nonlinear part and its identification. The identification model under consideration is defined in an abstract framework, with very weak hypotheses, so that the proposed approach has a large scope. To highlight the method, a class of dynamic Volterra models including some hybrid models such as dynamic inclusions is considered for application. Copyright © 2016 John Wiley & Sons, Ltd.