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Robust Fault Detection of Nonlinear Singular Markov Jump Systems with Partially Unknown Information

机译:具有部分未知信息的非线性单数马尔可夫跳转系统的强大故障检测

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The problem of robust fault detection (RFD) for nonlinear singular Markovian jump systems (NSMJLSs) with partly unknown transition probabilities is investigated in the paper. The RFD observer (RFDO) system and the dynamics of error generator are constructed. By Lyapunov function approach, the proposed method reduces the conservatism compared with the existing ones. Moreover, the H_∞ performance index is proposed to minimize the influence of the unknown disturbances. Sufficient conditions on the existence of RFDO are established and given in terms of linear matrix inequalities (LMIs). Finally, a simulation example is given to illustrate that the proposed RFDO can detect the faults correctly and shortly after the occurrence.
机译:在纸上研究了非线性单数马尔维亚跳转系统(NSMJLS)的鲁棒故障检测(RFD)的问题。构建RFD观察者(RFDO)系统和误差发生器的动态。通过Lyapunov功能方法,所提出的方法与现有的方法降低了保守主义。此外,提出了H_∞性能指标,以最大限度地减少未知干扰的影响。在线性矩阵不等式(LMI)而建立并给出了RFDO存在的充分条件。最后,给出了模拟示例来说明所提出的RFDO可以在发生后正确且不久地检测故障。

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