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Robust fault detection in hybrid systems using set-membership parameter estimation

机译:使用集合成员参数估计在混合系统中进行可靠的故障检测

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摘要

Hybrid systems exhibit continuous and discrete dynamics and are encountered in many complex and safety-critical systems. Due to their complex nature, the fault diagnosis task becomes very challenging. In this paper, we present a method to perform fault detection with a nonlinear hybrid system using set-membership parameter estimation in a bounded-error framework. Our method relies on a consistency test between the feasible parameter set as computed in normal fault-free operation or given as nominal, and the feasible parameter set as estimated during on-line operation over a given time horizon. Hence, a fault is detected if the feasible set for the parameter vector estimated online is inconsistent with nominal values. An illustrative example is presented.
机译:混合动力系统表现出连续和离散的动态,在许多复杂和安全关键型系统中都会遇到。由于其复杂性,故障诊断任务变得非常具有挑战性。在本文中,我们提出了一种在有界误差框架中使用集合隶属度参数估计对非线性混合系统进行故障检测的方法。我们的方法依赖于在正常无故障运行中计算或给出的可行参数集与在给定时间范围内在线运行期间估计的可行参数集之间的一致性测试。因此,如果在线估计的参数向量的可行集与标称值不一致,则检测到故障。给出了一个说明性的例子。

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