基于区间观测器的线性变参数系统鲁棒传感器故障检测

T. Chevet, T. N. Dinh, J. Marzat, T. Raïssi
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引用次数: 2

摘要

针对具有不可测参数向量且受未知有界扰动的连续时间线性变参数系统,提出了一种新的区间观测器。假设参数变化矩阵是元素有界的。该观测器用于计算所谓的残差区间,通过检查区间中是否包含零来用于传感器故障检测。为了减弱系统不确定性对故障可检测性的影响,引入了附加加权矩阵和不同的上下观测器增益,提供了比经典区间观测器策略更大的自由度。此外,还提出了一个$L_{\infty}$过程来调整观测器增益的值,该过程易于修改以在估计算法中引入额外的约束。仿真结果表明了所提故障检测策略的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Robust Sensor Fault Detection for Linear Parameter-Varying Systems using Interval Observer
This paper proposes a new interval observer for continuous-time linear parameter-varying systems with an unmeasurable parameter vector subject to unknown but bounded disturbances. The parameter-varying matrices are assumed to be elementwise bounded. This observer is used to compute a so-called residual interval used for sensor fault detection by checking if zero is contained in the interval. To attenuate the effect of the system's uncertainties on the detectability of faults, additional weighting matrices and different upper and lower observer gains are introduced, providing more degrees of freedom than the classical interval observer strategies. In addition, a $L_{\infty}$ procedure is proposed to tune the value of the observer gains, this procedure being easy to modify to introduce additional constraints on the estimation algorithm. Simulations are run to show the efficiency of the proposed fault detection strategy.
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