頁籤選單縮合
題 名 | A New Approach to Optimal and Self-Tuning Filtering, Smoothing and Prediction for Discrete-Time Systems |
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作 者 | Zhang,Huanshui; Xie,Lihua; Soh,Yeng Chai; | 書刊名 | Asian Journal of Control |
卷 期 | 3:3 2001.09[民90.09] |
頁 次 | 頁234-239 |
分類號 | 448.942 |
關鍵詞 | Linear discrete stochastic systems; Optimal estimation; Self-tuning estimation; Innovation analysis method; |
語 文 | 英文(English) |
英文摘要 | A new approach to optimal and self-tuning state estimation of linear discrete time-invariant systems is presented, using projection theory and innovation analysis method in time domain. The optimal estimators are calculated by means of spectral factorization. The filter, predictor, and smoother are given in a unified form. Comparisons are made to the previously known techniques such as the Kalman filtering and the polynomial method initiated by Kucera. When the noise covariance matrices are not available, self-tuning estimators are obtained through the identification of an ARMA innovation model. The self-tuning estimator asymptotically converges to the optimal estimator. |
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