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K-Loss Robust Diagnosability of Discrete-Event Systems

机译：用于离散事件系统的K损失稳健诊断性

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摘要

Recently, the problem of robust diagnosis against intermittent loss of observations (RDILO) has been proposed in the literature, where a model for the plant subject to intermittent loss of event observations is presented, and fault diagnosability verification methods are proposed based on the new plant model. In this method it is assumed that some sensors of the system are reliable and are always capable of communicating their readings to the diagnoser, while the other sensors, or communication channels between sensors and diagnoser, are subject to intermittent failures. The case of unreliable communication of all observable events cannot be addressed using the RDILO since the model of the plant subject to intermittent loss of event observations also represents their permanent losses. In this paper, we formulate a different problem of robust diagnosis that considers only intermittent loss of observations, which allows considering the case that all communication channels between the plant and diagnoser are not reliable. The new formulation leads to a different notion of robust diagnosability, called K-loss robust diagnosability.
机译：最近，在文献中提出了针对间歇性观察失去观察失去观察丧失的鲁棒诊断问题，其中提出了植物的模型，以进行间歇性事件观察的损失，基于新工厂提出故障诊断验证方法模型。在该方法中，假设系统的一些传感器是可靠的并且始终能够将它们的读数传送到诊断器，而其他传感器或传感器和诊断器之间的通信信道受到间歇故障。由于植物可能受到间歇性事件观察的损失的可能性，因此不能使用rdilo来解决所有可观察事件的不可靠通信的情况也代表其永久性损失。在本文中，我们制定了强大的诊断问题，仅考虑了观察的间歇性损失，这允许考虑植物和诊断器之间的所有通信信道不可靠的情况。新配方导致不同概念的稳健性诊断，称为K损失稳健诊断性。

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