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A simple approach to nonlinear estimation of physical systems

Mathematical and Computer Modelling

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Abstract

Recursive algorithms for estimating the states of nonlinear physical systems are developed. This requires some key hypotheses regarding the structure of the underlying processes. Members of this class of random processes have several desirable properties for the nonlinear estimation of random signals. An assumption is made about the form of the estimator, which may then take account of a wide range of applications. Under the above assumption, the estimation algorithm is mathematically suboptimal but effective and computationally attractive. It may be compared favorably to Taylor series-type filters, nonlinear filters which approximate the probability density by Edgeworth or Gram-Charlier series, as well as to conventional statistical linearization-type estimators. To link theory with practice, some numerical results for a simulated system are presented, in which the responses from the proposed and the extended Kalman algorithms are compared. ?? 1988.

Additional Publication Details

Publication type:
Article
Publication Subtype:
Journal Article
Title:
A simple approach to nonlinear estimation of physical systems
Series title:
Mathematical and Computer Modelling
Volume
11
Issue:
C
Year Published:
1988
Language:
English
Larger Work Type:
Article
Larger Work Subtype:
Journal Article
First page:
583
Last page:
588
Number of Pages:
6