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

机译:使用Set-Membership参数估计混合系统中的强大故障检测

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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:混合系统表现出连续和离散的动态,并且在许多复杂和安全关键系统中遇到。由于他们复杂的性质,故障诊断任务变得非常具有挑战性。在本文中,我们介绍了一种在界限错误框架中使用设定成员资格参数估计使用非线性混合系统执行故障检测的方法。我们的方法依赖于在正常无故障操作中计算的可行参数集之间的一致性测试,或者作为标称估计在给定时间范围内的在线操作期间估计的可行参数集。因此,如果在线估计的参数向量的可行设置与标称值不一致,则检测到故障。提出了说明性的示例。

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