Robust Filtering With Randomly Varying Sensor Delay: The Finite-Horizon Case
Robust Filtering With Randomly Varying Sensor Delay: The Finite-Horizon Case
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DOI：
10.1109/tcsi.2008.918009
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发表时间：
2009
期刊：
影响因子：
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通讯作者：
Fuwen Yang;Zidong Wang;Gang Feng;Xiao-Han Liu
中科院分区：
文献类型：
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作者：
Fuwen Yang;Zidong Wang;Gang Feng;Xiao-Han Liu
在本文中，我们考虑具有范数有界参数不确定性的延迟传感器测量的离散时变系统的鲁棒滤波问题。延迟的传感器测量被假设为满足伯努利随机二元分布定律的随机变量的线性函数。导出不确定随机参数系统的实际协方差的上限并将其用于估计方差约束。然后针对所有随机传感器延迟和允许的确定性不确定性，在滤波器参数上最小化这样的上限。结果表明，可以根据两个离散 Riccati 差分方程的解来获得所需的滤波器，该方程的形式适合在线应用中的递归计算。给出了一个说明性示例来显示所提出方法的适用性。
In this paper, we consider the robust filtering problem for discrete time-varying systems with delayed sensor measurement subject to norm-bounded parameter uncertainties. The delayed sensor measurement is assumed to be a linear function of a stochastic variable that satisfies the Bernoulli random binary distribution law. An upper bound for the actual covariance of the uncertain stochastic parameter system is derived and used for estimation variance constraints. Such an upper bound is then minimized over the filter parameters for all stochastic sensor delays and admissible deterministic uncertainties. It is shown that the desired filter can be obtained in terms of solutions to two discrete Riccati difference equations of a form suitable for recursive computation in online applications. An illustrative example is presented to show the applicability of the proposed method.