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Generalized System Information Fusion Wiener State Estimators

Posted on:2009-07-10Degree:MasterType:Thesis
Country:ChinaCandidate:C J RanFull Text:PDF
GTID:2208360245960070Subject:Control theory and control engineering
Abstract/Summary:PDF Full Text Request
Recently, the state estimation problems for descriptor (singular) systems have received great attention due to extensive application backgrounds, including electrical circuits, economics, robotics and aerospace etc. The information fusion filtering for the conventional systems has widely been applied in many fields. But the multisensor information fusion state estimation problem for descriptor systems is an open problem. For the linear discrete time-invariant stochastic descriptor system with multisensor, by the five different ways the state equation of the descriptor system can be transformed into five different non-recursive representations, which are the linear combination of input white noises, observation white noises and observations. Thus state estimation problem for descriptor systems is converted into white noise estimation and observation prediction problems. By the modem time series analysis method, based on the autoregressive moving average (ARMA) innovation model and white noise estimation theory, using the linear minimum variance optimal fusion rule weighted by matrices, diagonal matrices and scalars, the weighted fusion Wiener state estimators are presented, respectively. The fused filtering, smoothing, and prediction problems, and non-cause descriptor systems can be handled in a unified framework. The formulas of computing the variance and cross-covariance matrices among local estimation errors are presented, which are applied to compute the optimal weights. The accuracy of the fuser with matrix weights is higher than that of the fuser with scalar weights, and the accuracy of the fuser with diagonal matrix weights is between both of them, and the accuracy of fusers is higher than that of each local estimator. Many Monte Carlo simulation examples show their effectiveness.
Keywords/Search Tags:multisensor information fusion, weighted fusion, descriptor system, Wiener state estimator, modern time series analysis method
PDF Full Text Request
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