14th IFAC Symposium on System Identification, SYSID 2006

SYSID-2006 Paper Abstract

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Paper FrB2.3

Simandl, Miroslav (Univ. of West Bohemia in Pilsen), Dunik, Jindrich (Univ. of West Bohemia in Pilsen)

Design of Derivative-Free Smoothers and Predictors

Scheduled for presentation during the Regular Session "Filtering and Smoothing" (FrB2), Friday, March 31, 2006, 16:10−16:30, Banquet Room

14th IFAC Symposium on System Identification, March 29 - 31, 2006, Newcastle, Australia

This information is tentative and subject to change. Compiled on July 16, 2018

Keywords Bayesian Methods, Recursive Identification, Filtering and Smoothing

Abstract

Local state estimation approaches for nonlinear stochastic systems are treated. The unscented transformation and the Stirling’s polynomial interpolation, used in the design of the derivative-free Kalman filters, are briefly discussed. These approximation techniques are exploited to the design of the derivative-free smoothers and predictors. Some aspects of the different types of the derivative-free smoothers are analysed. The estimation qualities of the proposed estimators are illustrated in a numerical example.