Anticipative grid design in point-mass approach to nonlinear state estimation

Author

Simandl, Miroslav ; Královec, Jakub ; Söderström, Torsten

Author_Institution

Dept. of Cybern., Univ. of West Bohemia, Pilsen, Czech Republic

Volume

47

Issue

4

fYear

2002

fDate

4/1/2002 12:00:00 AM

Firstpage

699

Lastpage

702

Abstract

Numerical solution of the Bayesian recursive relations by the point-mass approach is treated. The stress is laid on the grid design as the main user design problem in this approach. An anticipative approach for finding a minimum sufficient number of grid points is developed, yielding a new adaptive algorithm reducing the computational operations without a loss of estimation accuracy. A numerical example is presented to compare the new algorithm with the standard point-mass technique and with a sequential importance sampling nonlinear filtering algorithm

Keywords

Bayes methods; adaptive systems; computational complexity; filtering theory; importance sampling; nonlinear filters; nonlinear systems; state estimation; Bayesian recursive relations; anticipative grid design; computational operations reduction; estimation accuracy; nonlinear state estimation; numerical solution; point-mass approach; point-mass technique; sequential importance sampling nonlinear filtering algorithm; Bayesian methods; Cybernetics; Density functional theory; Filtering algorithms; Function approximation; Grid computing; Monte Carlo methods; Sliding mode control; State estimation; Stochastic systems;

fLanguage

English

Journal_Title

Automatic Control, IEEE Transactions on

Publisher

ieee

ISSN

0018-9286

Type

jour

DOI

10.1109/9.995053

Filename

995053