论文标题

使用线性时间逻辑的不可靠传感器诊断离散事件系统的统一框架

A Uniform Framework for Diagnosis of Discrete-Event Systems with Unreliable Sensors using Linear Temporal Logic

论文作者

Dong, Weijie, Yin, Xiang, Li, Shaoyuan

论文摘要

在本文中,我们调查了受不可靠传感器的部分分离离散事件系统(DES)的可诊断性验证问题。在这种情况下,在每个事件发生时,由于测量噪声或可能的传感器故障,传感器读数可能是无确定性的。现有关于此主题的作品主要考虑特定类型的不可靠传感器,例如间歇性传感器故障,永久传感器故障或其组合的情况。在这项工作中,我们提出了一个新颖的\ emph {统一框架},以诊断为DES的性能,不仅是传感器故障,而且还具有非常一般的不可靠传感器类别。我们的方法是将线性时间逻辑(LTL)带有无限痕迹上的语义来描述传感器的可能行为。当传感器的行为满足LTL公式$φ$时,提出了一个新的$φ$ - 诊断性的概念作为存在诊断者的必要条件。提供有效的方法来验证这一概念。我们表明,我们的新概念$φ$ -DINASOMAINIDE归功于DES易于诊断的所有现有概念。此外,提出的框架是用户友好且灵活的,因为它根据应用程序的特定方案支持任意用户定义的不可靠的传感器类型。作为示例,我们提供了两个新的诊断性概念,这些诊断性使用我们的统一框架在文献中从未进行过研究。

In this paper, we investigate the diagnosability verification problem of partially-observed discrete-event systems (DES) subject to unreliable sensors. In this setting, upon the occurrence of each event, the sensor reading may be non-deterministic due to measurement noises or possible sensor failures. Existing works on this topic mainly consider specific types of unreliable sensors such as the cases of intermittent sensors failures, permanent sensor failures or their combinations. In this work, we propose a novel \emph{uniform framework} for diagnosability of DES subject to, not only sensor failures, but also a very general class of unreliable sensors. Our approach is to use linear temporal logic (LTL) with semantics on infinite traces to describe the possible behaviors of the sensors. A new notion of $φ$-diagnosability is proposed as the necessary and sufficient condition for the existence of a diagnoser when the behaviors of sensors satisfy the LTL formula $φ$. Effective approach is provided to verify this notion. We show that, our new notion of $φ$-diagnosability subsumes all existing notions of robust diagnosability of DES subject to sensor failures. Furthermore, the proposed framework is user-friendly and flexible since it supports an arbitrary user-defined unreliable sensor type based on the specific scenario of the application. As examples, we provide two new notions of diagnosability, which have never been investigated in the literature, using our uniform framework.

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