Hybrid Methods in Engineering Modeling, Programming, Analysis, Animation

ISSN for PRINT: 1099-2391

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2000, Volume2

Issue 3

110 pages

Issue price - $125.00

A. G. Nowosad
Instituto Nacional de Pesquisas Espaciais (INPE), Caixa Postal 515 12201-970, Sao Jose dos Campos (SP), Brazil

A. Rios Neto
Instituto Nacional de Pesquisas Espaciais (INPE), Caixa Postal 515 12201-970, Sao Jose dos Campos (SP), Brazil

Haroldo F. de Campos Velho
Institute Nacional de Pesquisas Espaciais (INPE), Caixa Postal 515, 12201-970 São José dos Campos - SP, Brazil

An Adaptive Extended Kalman Filter is used for data assimilation in two nonlinear dynamical systems: the Lorenz system in chaotic state and the computational model DYNAMO for the atmosphere. This approach does not require the modeling error to be stationary and uses a Linear Kalman Filter to estimate this error. This method is compared to the methods using Laplace transform, and Linear and Extended Kalman Filters. The conclusion was that the choice between using Laplace transform and Adaptive Kalman Filter assimilation methods for DYNAMO depended on whether one was willing to completely reject high-frequency information or not. When that information was considered useless, the Laplace filtering eliminated it better than the Kalman filtering. Otherwise, Kalman assimilated it better than Laplace.

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