filtering for stochastic systems driven by Poisson processes
filtering for stochastic systems driven by Poisson processes
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DOI：
10.1080/00207179.2014.936510
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发表时间：
2015-01
影响因子：
2.1
通讯作者：
Bo Song;Zhengguang Wu;Ju H. Park;Guodong Shi;Ya Zhang
中科院分区：
文献类型：
--
作者：
Bo Song;Zhengguang Wu;Ju H. Park;Guodong Shi;Ya Zhang
本文研究了泊松过程驱动的随机系统的过滤问题。利用可预测投影算子、对偶可预测投影算子等鞅理论，将泊松过程的随机积分的期望转化为勒贝格积分的期望。然后，在此基础上，本文设计了一种滤波器，使得滤波误差系统均方渐近稳定，并满足规定的性能水平。最后，给出了一个仿真例子来说明所提出的滤波方案的有效性。
This paper investigates the filtering problem for stochastic systems driven by Poisson processes. By utilising the martingale theory such as the predictable projection operator and the dual predictable projection operator, this paper transforms the expectation of stochastic integral with respect to the Poisson process into the expectation of Lebesgue integral. Then, based on this, this paper designs an filter such that the filtering error system is mean-square asymptotically stable and satisfies a prescribed performance level. Finally, a simulation example is given to illustrate the effectiveness of the proposed filtering scheme.