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Anisotropic Estimator Design for Time Varying System with Measurement Dropouts

机译:测量辍学时间变化系统的各向异性估计设计

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In this paper, the anisotropy-based filtering problem is studied for a class of linear discrete time varying finite horizon systems with measurement data packet dropout. The measurement packet dropout phenomenon is considered to be random, and is modeled as binary switching sequence of independent identically distributed scalar random variables. The estimator is designed to satisfy the upper bound constraint on the anisotropic norm chosen to quantitatively describe the performance index of the input-to-error system over the finite horizon. Given the measurements and estimates of the system outputs, the filter parameters are parameterized by means of the solution to a set of discrete linear (with a minor exception of one) matrix inequalities.
机译:在本文中,研究了基于各向异性的过滤问题,用于一类具有测量数据分组丢失的一类线性离散时间变化有限的有限系统。 测量分组丢失现象被认为是随机的,并且被建模为独立相同分布的标量变量的二进制切换序列。 估计器旨在满足所选择的各向异性标准的上限约束,以定量地描述在有限范围内输入到误差系统的性能指标。 鉴于系统输出的测量和估计,滤波器参数通过解决方案参数化为一组离散线性(具有一个)矩阵不等式的一个离散线性(具有次要异常)。

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