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https://hdl.handle.net/2440/78783
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Type: | Journal article |
Title: | Approximate finite-dimensional filtering for polynomial states over polynomial observations |
Author: | Basin, M. Shi, P. Calderon-Alvarez, D. |
Citation: | International Journal of Control, 2010; 83(4):724-730 |
Publisher: | Taylor & Francis Ltd |
Issue Date: | 2010 |
ISSN: | 0020-7179 1366-5820 |
Statement of Responsibility: | Michael Basin, Peng Shi and Dario Calderon-Alvarez |
Abstract: | In this article, the mean-square filtering problem for polynomial system states over polynomial observations is studied proceeding from the general expression for the stochastic Ito differentials of the mean-square estimate and the error variance. In contrast to the previously obtained results, this article deals with the general case of nonlinear polynomial states and observations. As a result, the Ito differentials for the mean-square estimate and error variance corresponding to the stated filtering problem are first derived. The procedure for obtaining an approximate closed-form finite-dimensional system of the filtering equations for any polynomial state over observations with any polynomial drift is then established. In the example, the obtained closed-form filter is applied to solve the third-order sensor filtering problem for a quadratic state, assuming a conditionally Gaussian initial condition for the extended third-order state vector. The simulation results show that the designed filter yields a reliable and rapidly converging estimate. © 2010 Taylor & Francis. |
Keywords: | filtering nonlinear systems stochastic systems |
Rights: | © 2010 Taylor & Francis |
DOI: | 10.1080/00207170903390179 |
Published version: | http://dx.doi.org/10.1080/00207170903390179 |
Appears in Collections: | Aurora harvest 4 Electrical and Electronic Engineering publications |
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