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CLC number: TP273

On-line Access: 2012-11-02

Received: 2012-04-03

Revision Accepted: 2012-07-03

Crosschecked: 2012-10-12

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Journal of Zhejiang University SCIENCE C 2012 Vol.13 No.11 P.850-858


Uniform modeling of parameter dependent nonlinear systems

Author(s):  Najmeh Eghbal, Naser Pariz, Ali Karimpour

Affiliation(s):  Department of Electrical Engineering, Ferdowsi University of Mashhad, P. O. Box 91775-1111, Iran

Corresponding email(s):   najmeh.eghbal@gmail.com

Key Words:  Parameter dependent nonlinear systems, Approximation method, Parameter dependent piecewise affine systems, Modeling

Najmeh Eghbal, Naser Pariz, Ali Karimpour. Uniform modeling of parameter dependent nonlinear systems[J]. Journal of Zhejiang University Science C, 2012, 13(11): 850-858.

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author="Najmeh Eghbal, Naser Pariz, Ali Karimpour",
journal="Journal of Zhejiang University Science C",
publisher="Zhejiang University Press & Springer",

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%T Uniform modeling of parameter dependent nonlinear systems
%A Najmeh Eghbal
%A Naser Pariz
%A Ali Karimpour
%J Journal of Zhejiang University SCIENCE C
%V 13
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%P 850-858
%@ 1869-1951
%D 2012
%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.C1200096

T1 - Uniform modeling of parameter dependent nonlinear systems
A1 - Najmeh Eghbal
A1 - Naser Pariz
A1 - Ali Karimpour
J0 - Journal of Zhejiang University Science C
VL - 13
IS - 11
SP - 850
EP - 858
%@ 1869-1951
Y1 - 2012
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/jzus.C1200096

This paper addresses the problem of approximating parameter dependent nonlinear systems in a unified framework. This modeling has been presented for the first time in the form of parameter dependent piecewise affine systems. In this model, the matrices and vectors defining piecewise affine systems are affine functions of parameters. modeling of the system is done based on distinct spaces of state and parameter, and the operating regions are partitioned into the sections that we call ‘multiplied simplices’. It is proven that this method of partitioning leads to less complexity of the approximated model compared with the few existing methods for modeling of parameter dependent nonlinear systems. It is also proven that the approximation is continuous for continuous functions and can be arbitrarily close to the original one. Next, the approximation error is calculated for a special class of parameter dependent nonlinear systems. For this class of systems, by solving an optimization problem, the operating regions can be partitioned into the minimum number of hyper-rectangles such that the modeling error does not exceed a specified value. This modeling method can be the first step towards analyzing the parameter dependent nonlinear systems with a uniform method.

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article


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