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Publication Date:
February 2004
ISSN:
1569-3945
DOI:
10.1515/156939404773972752

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Editor-in-Chief: Kabanikhin, Sergey I.

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Nonlinear set-membership estimation: A support vector machine approach

K. J. Keesman / R. Stappers

Systems and Control Group, Wageningen University, P.O. Box 43, 6700 AA Wageningen, The Netherlands. E-mail: karel.keesman@wur.nl

Citation Information: Journal of Inverse and Ill-posed Problems jiip. Volume 12, Issue 1, Pages 27–41, ISSN (Online) 1569-3953, ISSN (Print) 0928-0219, DOI: 10.1515/156939404773972752,

Publication History:
Published Online:

In this paper a support vector machine (SVM) approach for characterizing the feasible parameter set (FPS) in non-linear set-membership estimation problems is presented. It iteratively solves a regression problem from which an approximation of the boundary of the FPS can be determined. To guarantee convergence to the boundary the procedure includes a no-derivative line search and for an appropriate coverage of points on the FPS boundary it is suggested to start with a sequential box pavement procedure. The SVM approach is illustrated on a simple sine and exponential model with two parameters and an agro-forestry simulation model.

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