Title :
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
fDate :
4/1/2002 12:00:00 AM
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;
Journal_Title :
Automatic Control, IEEE Transactions on