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Fault Detection Architecture for Proprioceptive Sensors based on a Multi Model Approach and Fuzzy Logic Decisions

机译:基于多模型方法和模糊逻辑决策的预读者故障检测架构

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In this paper a new fault detection architecture will be presented. Inspired by multi-model data fusion algorithms and fuzzy logic decisions, it consists in the comparison between the estimation of a dynamic mode using each sensor independently. This method is used to deal with important non-linearity and strong interaction with the environment usually encountered in the domain of the intelligent vehicles localization. The concept of analytic redundancy is also used to ignore model uncertainties.
机译:本文将呈现新的故障检测架构。灵感来自多模型数据融合算法和模糊逻辑决策,它在独立地使用每个传感器的动态模式估计之间的比较中。这种方法用于处理重要的非线性和与智能车辆本地化领域通常遇到的环境的强烈互动。分析冗余的概念也用于忽略模型不确定性。

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