Optimal Linear Estimation for Stochastic Uncertain Systems with Multiple Packet Dropouts and Delays
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摘要: 研究了带多丢包和滞后网络化随机不确定系统的最优线性估计问题. 通过白色乘性噪声来描述系统参数的随机不确定性. 通过一组满足Bernoulli分布的随机变量来描述数据传输过程中发生的丢包和滞后现象. 应用新息分析方法, 设计了线性最小方差意义下的最优线性估值器, 包括滤波器, 预报器和平滑器. 给出了稳态估值器存在的一个充分条件. 仿真例子验证了其有效性.Abstract: This paper is concerned with the optimal linear estimation problem for networked stochastic uncertain systems with multiple packet dropouts and delays. The random uncertainties of system parameters are described by white multiplicative noises. The phenomena of packet dropouts and delays in data transmission are described by a group of Bernoulli distributed random variables. Using an innovation analysis method, the optimal linear estimators including filter, predictor and smoother are presented in a linear minimum variance sense. A sufficient condition for the existence of the steady-state estimators is given. An example shows the effectiveness of the optimal linear estimators.
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