Robust filtering under randomly varying sensor delay with variance constraints
Robust filtering under randomly varying sensor delay with variance constraints
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DOI：
10.1109/tcsii.2004.829572
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发表时间：
2003-09
期刊：
影响因子：
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通讯作者：
Zidong Wang;D. Ho;Xiaohui Liu
中科院分区：
文献类型：
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作者：
Zidong Wang;D. Ho;Xiaohui Liu
研究了一类具有随机变化传感器时滞的线性不确定离散随机系统的滤波问题。范数有界的参数不确定性进入状态空间模型的系统矩阵。系统的测量受到随机变化的传感器延迟，这经常发生在通过网络的信息传输。所解决的问题是一个线性滤波器的设计，使得对于所有容许的参数不确定性和所有概率传感器延迟，滤波过程的误差状态是均方有界的，并且每个状态的估计误差的稳态方差不超过个人规定的上限。我们证明了所考虑的过滤问题可以有效地解决，如果有正定解的代数Riccati类不等式或线性矩阵不等式的夫妇。我们还描述了所需的鲁棒滤波器的一些自由参数。一个说明性的数值例子是用来证明所提出的设计方法的实用性和灵活性。
This paper deals with a new filtering problem for linear uncertain discrete-time stochastic systems with randomly varying sensor delay. The norm-bounded parameter uncertainties enter into the system matrix of the state space model. The system measurements are subject to randomly varying sensor delays, which often occur in information transmissions through networks. The problem addressed is the design of a linear filter such that, for all admissible parameter uncertainties and all probabilistic sensor delays, the error state of the filtering process is mean square bounded, and the steady-state variance of the estimation error for each state is not more than the individual prescribed upper bound. We show that the filtering problem under consideration can effectively be solved if there are positive definite solutions to a couple of algebraic Riccati-like inequalities or linear matrix inequalities. We also characterize the set of desired robust filters in terms of some free parameters. An illustrative numerical example is used to demonstrate the usefulness and flexibility of the proposed design approach.