Journal
AUTOMATICA
Volume 36, Issue 11, Pages 1627-1638Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/S0005-1098(00)00089-3
Keywords
state estimation; nonlinear filters; interpolation algorithms; multivariable polynomials; extended Kalman filters; parameter estimation
Ask authors/readers for more resources
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. (C) 2000 Elsevier Science Ltd. All rights reserved.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available