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Robust H_∞ filtering for networked stochastic systems with randomly occurring sensor nonlinearities and packet dropouts

机译:具有随机发生的传感器非线性和丢包的网络随机系统的鲁棒H_∞滤波

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摘要

In this paper, the robust H_∞ filtering problem is investigated for networked stochastic systems with norm bounded uncertainties and imperfect multiple transmitted measurements. The considered imperfect measurements contain randomly occurring sensor nonlinearities and packet dropouts, which are represented by multiple independent Markov chains with partially unknown transition probabilities. A one to one mapping is constructed to map the multiple independent Markov chains to an augmented one for facilitating the resultant system analysis. A sufficient condition is established to guarantee the exponential mean-square stability with fast decay rate and a certain H_∞ performance level of the filtering error systems. Then, the parameters of the full-order filter are expressed in terms of linear matrix inequalities (LMIs). Finally, a numerical example is shown to demonstrate the effectiveness of the proposed method.
机译:本文研究了具有范数界不确定性和不完善多次传输测量的网络随机系统的鲁棒H_∞滤波问题。认为不完善的测量包含随机发生的传感器非线性和数据包丢失,这由多个独立的马尔可夫链表示,其转移概率部分未知。构建一对一映射以将多个独立的马尔可夫链映射到增强的映射,以便于进行结果系统分析。建立了充分的条件,以保证具有快速衰减率和一定的H_∞性能水平的滤波误差系统的指数均方稳定性。然后,以线性矩阵不等式(LMI)表示全阶滤波器的参数。最后,通过算例说明了所提方法的有效性。

著录项

  • 来源
    《Signal processing》 |2013年第7期|1794-1803|共10页
  • 作者单位

    State Key Laboratory of Industrial Control Technology, Institute of Cyber-Systems and Control, Zhejiang University, Yuquan Campus, Hangzhou Zhejiang 310027, PR China;

    State Key Laboratory of Industrial Control Technology, Institute of Cyber-Systems and Control, Zhejiang University, Yuquan Campus, Hangzhou Zhejiang 310027, PR China;

    Department of Mechanical Engineering, Dalhousie University, P.O. Box 15000, Halifax, Nova Scotia, Canada B3H 4R2;

    State Key Laboratory of Industrial Control Technology, Institute of Cyber-Systems and Control, Zhejiang University, Yuquan Campus, Hangzhou Zhejiang 310027, PR China;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Robust H_∞ filtering; Networked stochastic systems; Markov chain; Sensor nonlinearity; Packet dropout;

    机译:强大的H_∞滤波;网络随机系统;马尔可夫链传感器非线性;丢包;

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