The Adaptive Kalman Filter Based on Improved Variable Oblivion Factor Least Square Arithmetic

Author:

Song Yu1

Affiliation:

1. Beijing Normal University

Abstract

Adopting improved variable oblivion factor least square arithmetic to real-time amend Kalman’s state transfer matrix, we put Maple Dam reservoir flood forecast real-time adjustment for example, then apply and compare with other ways. The result shows this arithmetic is preferable.

Publisher

Trans Tech Publications, Ltd.

Subject

General Engineering

Reference11 articles.

1. Kalman R E.A new approach to linear filtering and prediction problems.Trans.ASME, J.Basic Eng., 82(1960), p.34~45.

2. Hino M.Runoff Forecasts by Linear Predictive Filter.Proc.ASCE, J.Hyd.Div., 96(1970), p.681~701.

3. Hino M.On-line prediction of a hydrologic system. Presented at XV Congre of IAHR, Istanbul(1973).

4. Wood E F and Szollosi-Nagy A.An Adaptive Algorithm for Analyzing Short Term structural and Parameter Changes in Hydrologic Prediction Models[J].Water Resour.Res.14(1978), p.575~581.

5. LI Shu-jin,LI Wen-hua.Parameter estimation of time-varying structures by the adaptive Kalman filter[J].Journal of Guangxi University (Nat Sci Ed), 29(2004), pp.146-149.

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