未知输入系统的分布式未知输入滤波

C. Hsieh
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引用次数: 1

摘要

众所周知,对于无模型未知输入滤波(MUIF),未知输入通常是用多步延迟重构的,这可能会产生多步延迟状态和未知输入估计。这对于实时状态估计问题显然是不切实际的。为了解决这一问题,本文首先针对特定的网络拓扑结构提出了一种分布式多步延迟状态和输入估计器(DMSDSIE)。然后,开发了基于DMSDSIE的某MUIF应用的实时状态估计器设计。本研究强调了通过网络应用分布式滤波来缓解一般同步输入和状态估计问题的时延估计问题的可能性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Distributed Unknown Input Filtering for Systems with Unknown Inputs
It is well known that, for model-free unknown input filtering (MUIF) the unknown inputs are generally reconstructed with a multi-step delay, which may yield multi-step delayed state and unknown input estimates. This certainly is unpractical for real-time state estimation problems. To solve this problem, the paper first proposes a distributed multi-step-delay state and input estimator (DMSDSIE) for a specific topology of network. Then, a real-time state estimator design of a certain MUIF application based on the DMSDSIE is developed. This research highlights a possibility to apply distributed filtering through a network to alleviate the time-delay estimation problem of a general simultaneous input and state estimation problem.
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