On-line estimation of nonlinear physical systems
Mathematical Geology
By: G. Christakos
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Abstract
Recursive algorithms for estimating states of nonlinear physical systems are presented. Orthogonality properties are rediscovered and the associated polynomials are used to linearize state and observation models of the underlying random processes. This requires some key hypotheses regarding the structure of these processes, which may then take account of a wide range of applications. The latter include streamflow forecasting, flood estimation, environmental protection, earthquake engineering, and mine planning. The proposed estimation algorithm 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. Moreover, the method has several advantages over nonrecursive estimators like disjunctive kriging. To link theory with practice, some numerical results for a simulated system are presented, in which responses from the proposed and extended Kalman algorithms are compared. ?? 1988 International Association for Mathematical Geology.
| Publication type | Article |
|---|---|
| Publication Subtype | Journal Article |
| Title | On-line estimation of nonlinear physical systems |
| Series title | Mathematical Geology |
| DOI | 10.1007/BF00918881 |
| Volume | 20 |
| Issue | 2 |
| Year Published | 1988 |
| Language | English |
| Publisher location | Kluwer Academic Publishers-Plenum Publishers |
| Larger Work Type | Article |
| Larger Work Subtype | Journal Article |
| Larger Work Title | Mathematical Geology |
| First page | 111 |
| Last page | 133 |
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