5 research outputs found

    Exploiting structure in piecewise affine identification of LFT systems

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    Identification of interconnected systems is a challenging problem in which it is crucial to exploit the available knowledge about the interconnection structure. In this paper, identification of discrete-time nonlinear systems composed by interconnected linear and nonlinear systems, is addressed. An iterative identification procedure is proposed, which alternates the estimation of the linear and the nonlinear components. Standard identification techniques are applied to the linear subsystem, whereas recently developed piecewise affine (PWA) identification techniques are employed for modelling the nonlinearity. A numerical example analyzes the benefits of the proposed structure-exploiting identification algorithm compared to applying black-box PWA identification techniques to the overall system

    Η μέθοδος των Πεπερασμένων Στοιχείων για Ελλειπτικές Μερικές Διαφορικές Εξισώσεις και εφαρμογή στην εξίσωση Stokes.

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    100 σ.Σκοπός της διπλωματικής εργασίας ήταν η επίλυση της εξίσωσης Stokes με τη μέθοδο των Πεπερασμένων Στοιχείων.The purpose of this diploma thesis was the solution of Stokes equation using the method of Finite Elements.Μαριάννα Ε. Πέπον

    Identification of piecewise affine LFR models of interconnected systems

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    Identification of interconnected systems is a challenging problem in which it is crucial to exploit the available knowledge about the interconnection structure. This paper addresses the identification of discrete-time dynamical models in linear fractional representation form, composed by the interconnection of a linear time-invariant block and a static nonlinearity. An iterative identification approach is adopted, which alternates the estimation of the linear and the nonlinear components. Standard identification techniques are applied to the linear part, whereas recently developed piecewise affine identification techniques are employed for modeling the static nonlinearity. The proposed method takes advantage of the interconnection structure to identify models which are more accurate and often much simpler than those obtained when applying black-box piecewise affine identification techniques to the overall system. This is demonstrated through the application of the adopted identification algorithm to the silverbox problem, a popular real-life benchmark in nonlinear system identification
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