Robust fault estimation for singularly perturbed systems with Lipschitz nonlinearity

Robust fault estimation for singularly perturbed systems with Lipschitz nonlinearity
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具有 Lipschitz 非线性的奇异扰动系统的鲁棒故障估计

DOI:
10.1016/j.franklin.2016.01.009
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发表时间:
2016-03
期刊:
Journal of the Franklin Institute
影响因子:
--
通讯作者:
Zhang Yong
Zhang Yong
中科院分区:
其他
文献类型:
--
作者:
Liu Dan;Yang Ying;Zhang Yong

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本文研究了Lipschitz非线性奇异摄动系统在传感器故障下的故障估计问题。针对导数有界的故障,提出了一种鲁棒故障估计方法。利用该方法,所提出的故障估计器最小化不确定性对估计误差的影响,同时最大化系统的稳定界。具体地说,首先以线性矩阵不等式的形式给出了所提出的故障估计器存在的充分条件。该条件使故障估计器对给定H∞性能指标的不确定性具有鲁棒性。然后,通过推导一种改进的多目标优化算法,保证了最大的稳定界和最佳的不确定性衰减能力。最后以电枢控制直流电动机为例说明了该方法的有效性。
In this paper, observer-based fault estimation problem is addressed for Lipschitz nonlinear singularly perturbed systems with respect to sensor faults. A robust fault estimation scheme is presented to estimate faults whose derivative is bounded. With this method, the proposed fault estimator minimizes the effect of uncertainty on the estimation error and maximizes stability bound of the system simultaneously. To be specific, a sufficient condition for existence of the proposed fault estimator is firstly derived in the form of LMIs. This condition enables the fault estimator to be robust to uncertainty in terms of a prescribed H∞ performance index. Then, the largest stability bound and the best uncertainty attenuation capacity are guaranteed by deriving a modified multi-objective optimal algorithm. An armature-controlled DC motor example is finally given to illustrate the effectiveness of the proposed scheme.
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发表时间: 2004-11
影响因子: 6.8
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