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Distributed estimation of non-linear functions of the state vector for multisensory continuous-time linear systems

机译:多传感器连续时间线性系统状态向量非线性函数的分布式估计

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摘要

This study focuses on fusion algorithms for the estimation of a non-linear function of the state vector in a multisensory continuous-time stochastic system. The non-linear function of the state (NFS) represents a non-linear multivariate function of state variables, which can indicate useful information of a target system for control. To estimate a NFS using multisensory information, they propose one centralised and three distributed estimation fusion algorithms. For multivariate polynomial functions, they derive a closed-form estimation procedure. In the general case, an unscented transformation is used for evaluation of the fusion estimate of an NFS. The subsequent application of the proposed fusion estimators to a linear stochastic system within a multisensor environment demonstrates their effectiveness.
机译:这项研究的重点是融合算法,用于估计多传感器连续时间随机系统中状态向量的非线性函数。状态的非线性函数(NFS)表示状态变量的非线性多元函数,可以指示目标系统的有用信息进行控制。为了使用多传感器信息估计NFS,他们提出了一种集中式和三种分布式估计融合算法。对于多元多项式函数,它们推导了一种封闭形式的估计程序。通常,将无味的变换用于评估NFS的融合估计。拟议的融合估计量在多传感器环境中的线性随机系统上的后续应用证明了它们的有效性。

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