Brief paper: Parameter identification for nonlinear systems: Guaranteed confidence regions through LSCR

  • Authors:

  • Marco Dalai;Erik Weyer;Marco C. Campi

  • Affiliations:

  • Department of Electrical Engineering and Automation, University of Brescia, Via Branze 38, 25123 Brescia, Italy;Department of Electrical and Electronic Engineering, The University of Melbourne, Parkville VIC 3010, Australia;Department of Electrical Engineering and Automation, University of Brescia, Via Branze 38, 25123 Brescia, Italy

  • Venue:
  • Automatica (Journal of IFAC)
  • Year:
  • 2007

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Abstract

In this paper we consider the problem of constructing confidence regions for the parameters of nonlinear dynamical systems. The proposed method uses higher order statistics and extends the LSCR (leave-out sign-dominant correlation regions) algorithm for linear systems introduced in Campi and Weyer [2005, Guaranteed non-asymptotic confidence regions in system identification. Automatica 41(10), 1751-1764. Extended version available at ]. The confidence regions contain the true parameter value with a guaranteed probability for any finite number of data points. Moreover, the confidence regions shrink around the true parameter value as the number of data points increases. The usefulness of the proposed approach is illustrated on some simple examples.