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strongtrackingfilter

于 2008-03-10 发布 文件大小:7KB
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  在目标被动式跟踪中广泛应用的伪量测变换估计器(PLE)具有良好的误差收敛性。然而由于等价噪声和状态的相关性,该估计器的估计是有偏的。提出的强跟踪滤波器(STF)通过强制白化残差具有自适应地校正估计偏差和迅速跟踪状态变化的能力。STF已经在非线性系统时滞估计、故障诊断与容错控制方面取得了很好的效果。(Passive target tracking is widely used in the pseudo-measurement transform estimator (PLE) has a good error convergence. However, due to the equivalent noise and the relevance of state, the estimator is a biased estimate of. Raised strong tracking filter (STF) has adopted mandatory bleaching residuals adaptively estimated bias correction and rapid tracking of the status change. STF has been estimated in the time-delay nonlinear systems, fault diagnosis and fault-tolerant control has been achieved very good results.)

文件列表:

FILTERNM.M
OBSE5.M
OBSE6.M
OBSE7.M
TDFNM.M

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