H∞ State estimation for stochastic state multiplicative systems

E. Gershon
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Abstract

The problem of $H_{\infty}$ state estimation is considered for uncertain polytopic linear discrete-time stochastic state-multiplicative systems. We first bring a unique version of the BRL for the latter systems which allows for vertex-dependent solution in the uncertain case. Following the BRL derivation, we solve the estimation problem for nominal systems which serves as a basis for extracting the filter parameters in the uncertain case. In both cases: the nominal and the uncertain cases, the filter parameters are extracted by a solving an LMI condition in the former case or a set of LMIs in the latter case, both of which depend on a minimal set of tuning parameters, thus greatly reduce the over-design. The theory presented is demonstrated by a numerical example.
随机状态乘法系统的H∞状态估计
研究了不确定多面体线性离散随机状态乘系统的$H_{\infty}$状态估计问题。我们首先为后一种系统带来了一个独特的BRL版本,它允许在不确定情况下的顶点依赖解决方案。根据BRL的推导,我们解决了标称系统的估计问题,为不确定情况下滤波器参数的提取提供了基础。在两种情况下:标称和不确定情况下,前者通过求解一个LMI条件提取滤波器参数,后者通过求解一组LMI条件提取滤波器参数,两者都依赖于一组最小的调优参数,从而大大减少了过度设计。通过数值算例验证了所提出的理论。
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