On-line estimation of nonlinear physical systems

Journal Article · Mon Feb 01 00:00:00 EST 1988 · J. Int. Assoc. Math. Geol.; (United States)

DOI:https://doi.org/10.1007/BF00918881· OSTI ID:6921403

Christakos, G

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.

• Research Organization: Kansas Geological Survey, Lawrence (USA)
• OSTI ID: 6921403
• Journal Information: J. Int. Assoc. Math. Geol.; (United States), Vol. 20:2
• Country of Publication: United States
• Language: English

Related Subjects

58 GEOSCIENCES
GEOPHYSICAL SURVEYS
DATA PROCESSING
NONLINEAR PROBLEMS
PROBABILISTIC ESTIMATION
ALGORITHMS
COMPUTERIZED SIMULATION
DIGITAL FILTERS
EARTHQUAKES
FLOODS
FORECASTING
HYDROLOGY
MINES
ON-LINE SYSTEMS
RECURSION RELATIONS
STATISTICAL MODELS
DISASTERS
MATHEMATICAL LOGIC
MATHEMATICAL MODELS
PROCESSING
SEISMIC EVENTS
SIMULATION
SURVEYS
UNDERGROUND FACILITIES
580202* - Geophysics- Volcanology- (1980-1989)