New developments in state estimation for nonlinear systems

Based on an interpolation formula, accurate state estimators for nonlinear systems can be derived. The estimators do not require derivative information which makes them simple to implement. State estimators for nonlinear systems are derived based on polynomial approximations obtained with a multi-di...

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Bibliographic Details
Published in:Automatica (Oxford) Vol. 36; no. 11; pp. 1627 - 1638
Main Authors: Nørgaard, Magnus, Poulsen, Niels K., Ravn, Ole
Format: Journal Article
Language:English
Published: Elsevier Ltd 01.11.2000
Subjects:
Extended Kalman filters
Interpolation algorithms
Multivariable polynomials
Nonlinear filters
Parameter estimation
State estimation
Parameter estimation
Interpolation algorithms
Multivariable polynomials
State estimation
Extended Kalman filters
Nonlinear filters
ISSN:0005-1098, 1873-2836
Online Access:Get full text
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Summary:Based on an interpolation formula, accurate state estimators for nonlinear systems can be derived. The estimators do not require derivative information which makes them simple to implement. State estimators for nonlinear systems are derived based on polynomial approximations obtained with a multi-dimensional interpolation formula. It is shown that under certain assumptions the estimators perform better than estimators based on Taylor approximations. Nevertheless, the implementation is significantly simpler as no derivatives are required. Thus, it is believed that the new state estimators can replace well-known estimators, such as the extended Kalman filter (EKF) and its higher-order relatives, in most practical applications.
ISSN:0005-1098
1873-2836
DOI:10.1016/S0005-1098(00)00089-3