基于NUIO的无人机作动器故障检测

张鹤; 钟麦英

doi:10.13700/j.bh.1001-5965.2014.0522

基于NUIO的无人机作动器故障检测

doi: 10.13700/j.bh.1001-5965.2014.0522

张鹤,
钟麦英^,

北京航空航天大学仪器科学与光电工程学院, 北京 100191

基金项目: 国家自然科学基金(61333005, 61174121, 61121003)

详细信息

作者简介:
张鹤(1988—),女,吉林长春人,硕士研究生,hezhang_buaa@126.com

通讯作者:
钟麦英(1965—),女,山东博兴人,教授,myzhong@buaa.edu.cn,主要研究方向为故障诊断与容错控制.

中图分类号: V448;TP273
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出版历程
- 收稿日期: 2014-08-22
- 修回日期: 2014-11-21
- 网络出版日期: 2015-07-20

NUIO based actuator fault detection for a UAV

ZHANG He,
ZHONG Maiying^,

School of Instrumentation Science and Opto-electronics Engineering, Beijing University of Aeronautics and Astronautics, Beijing 100191, China

摘要

摘要: 针对受未知气流干扰与随机噪声影响的无人机纵向系统进行作动器故障检测研究.在建立固定翼式无人机非线性系统纵向模型的基础上,设计了基于容积卡尔曼滤波(CKF)的非线性未知输入观测器(NUIO).通过构造未知输入观测器结构来解耦未知气流干扰对残差的影响,同时,CKF被算法用于求解观测器增益矩阵,实现了在未知气流干扰解耦情况下残差对随机噪声的鲁棒性.最后,利用残差χ²检验方法判断故障是否发生.仿真结果表明:此方法能有效解耦未知干扰对残差的影响,并快速、准确地检测出了无人机作动器故障.
- 无人机 /
- 故障检测 /
- 容积卡尔曼滤波 /
- 非线性未知输入观测器 /
- χ²检验
Abstract: The actuator fault detection for an unmanned aerial vehicle (UAV) longitudinal system with unknown atmospheric disturbances and stochastic noise was studied. Based on introducing a nonlinear longitudinal model of the fixed UAV, a residual generation was designed by employing a nonlinear unknown input observer (NUIO) which is based on cubature Kalman filter (CKF). The unknown input observer structure was constructed to decouple the unknown disturbances from residual. At the same time, the CKF was applied to calculate the gain matrix to achieve the requirement of robustness to noise. Finally, the occurrence of fault can be detected based on chi-square test about the residual sequence. The simulation results show that the proposed method can decouple the unknown disturbances from residual effectively and achieve the fast and accurate actuator fault detection.
- unmanned aerial vehicle (UAV) /
- fault detection /
- cubature Kalman filter (CKF) /
- nonlinear unknown input observer (NUIO) /
- chi-square test

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参考文献(20)

[1]	蔡志浩, 杨丽曼, 王英勋, 等.无人机全空域飞行影响因素分析[J].北京航空航天大学学报, 2011, 37(2): 176-184. Cai Z H, Yang L M, Wang Y X, et al.Analysis for whole airspace flight key factors of unmanned aerial vehicles[J].Journal of Beijing University of Aeronautics and Astronautics, 2011, 37(2): 176-184(in Chinese).
[2]	Hansen S, Blanke M.Control surface fault diagnosis for small autonomous aircraft[C]//Proceeding of the Australian Control Conference.Piscataway, NJ: IEEE Press, 2011: 185-190.
[3]	Panitsrisit P, Ruangwiset A.Sensor system for fault detection identification and accommodation of elevator of UAV[C]//Proceedings of SICE Annual Conference.Piscataway, NJ: IEEE Press, 2011: 1035-1040.
[4]	Freddi A, Longhi S, Monteriù A.A diagnostic Thau observer for a class of unmanned vehicles[J].Journal of Intelligent & Robotic Systems, 2012, 67(1): 61-73.
[5]	朱上翔.大气扰动及其对飞行的影响[J].航空学报, 1985, 6(2): 149-156. Zhu S X.Atmospheric turbulence and the effects on flight[J].Acta Aeronautica et Astronautica Sinica, 1985, 6(2): 149-156(in Chinese).
[6]	Frank P M, Ding X.Survey of robust residual generation and evaluation methods in observer-based fault detection systems[J].Journal of Process Control, 1997, 7(6): 403-424.
[7]	Bateman F, Noura H, Ouladsine M.An actuator fault detection, isolation and estimation system for an UAV using input observers[C]//Proceedings of European Control Conference.Piscataway, NJ: IEEE Press, 2007: 1805-1810.
[8]	Bateman F, Noura H, Ouladsine M.Active fault detection and isolation strategy for an unmanned aerial vehicle with redundant flight control surfaces[C]//Proceeding of the 16th Mediterranean Conference on Control and Automation.Piscataway, NJ: IEEE Press, 2008: 1246-1251.
[9]	Tousi M M, Khorasani K.Robust observer-based fault diagnosis for an unmanned aerial vehicle[C]//Proceeding of Systems Conference.Piscataway, NJ: IEEE Press, 2011: 428-434.
[10]	Yang X, Mejias L, Gonzalez F, et al.Nonlinear actuator fault detection for small-scale UASs[J].Journal of Intelligent & Robotic Systems, 2014, 73(1-4): 557-572.
[11]	Guillaume D, Hans P G.Efficient nonlinear actuator fault detection and isolation system for unmanned aerial vehicles[J].Journal of Guidance, Control & Dynamics, 2008, 31(1): 225-237.
[12]	Cen Z H, Noura H, Tri B S.Robust fault diagnosis for quadrotor UAVs using adaptive Thau observer[J].Journal of Intelligent & Robotic Systems, 2014, 73: 573-588.
[13]	Witczak M, Pretki P.Design of an extended unknown input observer with stochastic robustness techniques and evolutionary algorithms[J].International Journal of Control, 2007, 80(5): 749-762.
[14]	Zarei J, Shokri E.Robust sensor fault detection based on nonlinear unknown input observer[J].Measurement, 2014, 48: 355-367.
[15]	吴森堂, 费玉华.飞行控制系统[M].北京: 北京航空航天大学出版社, 2005: 64-70. Wu S T, Fei Y H.Flight control system[M].Beijing: Beihang University Press, 2005: 64-70(in Chinese).
[16]	Miller R H, Ribbens W B.The effects of icing on the longitudinal dynamics of an icing research aircraft, AIAA-1999-0636[R].Reston: AIAA, 1999.
[17]	Zhai R, Zhou Z, Zhang W, et al.Control and navigation system for a fixed-wing unmanned aerial vehicle[J].AIP Advances, 2014, 4(3): 1306.
[18]	Li Z, Ding J.Ground moving target tracking control system design for UAV surveillance[C]//Proceeding of International Conference on Automation and Logistics.Piscataway, NJ: IEEE Press, 2007: 1458-1463.
[19]	Arasaratnam I, Haykin S.Cubature Kalman filters[J].IEEE Transactions on Automatic Control, 2009, 54(6): 1254-1269.
[20]	Witczak M, Obuchowicz A, Korbicz J.Genetic programming based approaches to identification and fault diagnosis of nonlinear dynamic systems[J].International Journal of Control, 2002, 75(13): 1012-1031.