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基于中间观测器的鲁棒故障估计:在四旋翼飞行器中的应用

Robust Fault Estimation Using the Intermediate Observer: Application to the Quadcopter.

作者信息

Nguyen Ngoc Phi, Huynh Tuan Tu, Do Xuan Phu, Xuan Mung Nguyen, Hong Sung Kyung

机构信息

Department of Aerospace Engineering, Sejong University, Seoul 143-747 (05006), Korea.

Department of Electrical Engineering, Yuan Ze University, No. 135, Yuandong Road, Zhongli, Taoyuan 320, Taiwan.

出版信息

Sensors (Basel). 2020 Aug 31;20(17):4917. doi: 10.3390/s20174917.

DOI:10.3390/s20174917
PMID:32878080
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7506654/
Abstract

In this paper, an actuator fault estimation technique is proposed for quadcopters under uncertainties. In previous studies, matching conditions were required for the observer design, but they were found to be complex for solving linear matrix inequalities (LMIs). To overcome these limitations, in this study, an improved intermediate estimator algorithm was applied to the quadcopter model, which can be used to estimate actuator faults and system states. The system stability was validated using Lyapunov theory. It was shown that system errors are uniformly ultimately bounded. To increase the accuracy of the proposed fault estimation algorithm, a magnitude order balance method was applied. Experiments were verified with four scenarios to show the effectiveness of the proposed algorithm. Two first scenarios were compared to show the effectiveness of the magnitude order balance method. The remaining scenarios were described to test the reliability of the presented method in the presence of multiple actuator faults. Different from previous studies on observer-based fault estimation, this proposal not only can estimate the fault magnitude of the roll, pitch, yaw, and thrust channel, but also can estimate the loss of control effectiveness of each actuator under uncertainties.

摘要

本文针对存在不确定性的四旋翼飞行器提出了一种执行器故障估计技术。在以往的研究中,观测器设计需要匹配条件,但发现求解线性矩阵不等式(LMI)时这些条件很复杂。为克服这些局限性,本研究将一种改进的中间估计器算法应用于四旋翼飞行器模型,该算法可用于估计执行器故障和系统状态。利用李雅普诺夫理论验证了系统稳定性。结果表明系统误差是一致最终有界的。为提高所提出的故障估计算法的精度,应用了一种量级平衡方法。通过四个场景的实验验证了所提算法的有效性。比较了前两个场景以展示量级平衡方法的有效性。其余场景用于测试所提方法在存在多个执行器故障时的可靠性。与以往基于观测器的故障估计研究不同,本方案不仅可以估计滚转、俯仰、偏航和推力通道的故障大小,还可以估计在不确定性情况下每个执行器的控制有效性损失。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ec92/7506654/f6b7763a078e/sensors-20-04917-g018.jpg
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