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-  2017 

基于等价空间的无人机飞行控制系统故障检测
Parity space-based fault detection for unmanned aerial vehicle flight control systems

DOI: 10.6040/j.issn.1672-3961.0.2017.270

Keywords: 故障检测,等价空间,无人机,非线性系统,
nonlinear systems
,fault detection,parity space,unmanned aerial vehicle

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Abstract:

摘要: 无人机(unmanned aerial vehicle, UAV)飞行控制系统的故障检测,对于保障无人机的飞行安全具有重要意义。等价空间方法具有残差与未知初始状态解耦的优势,但随着等价空间阶次的提高,其在线计算量显著增大。针对上述问题,提出一种基于等价空间的无人机非线性飞行控制系统快速故障检测方法。建立无人机飞行控制系统的非线性故障模型,在针对线性离散时变系统的等价空间故障检测方法研究的基础上,利用Krein空间投影来实现残差评价函数的递推计算以减小故障检测计算量。以无人机空速管及升降舵故障检测为例,对算法进行了仿真试验验证。试验结果表明,提出的方法可以实现无人机飞行控制系统的快速故障检测。
Abstract: The fault detection(FD)for unmanned aerial vehicle(UAV)flight control system is of great significance to ensure the flight safety of UAV. The parity space approach has the advantage of the decoupling of residual and unknown initial state. However, the increasing of parity order will lead to heavy computational task. Aiming at these problems, a modified parity space approach was put forward for the FD of UAV nonlinear flight control systems. The nonlinear fault model of UAV flight control system was established. On the foundation of parity space approach for linear discrete time-varying systems, the projection in Krein space was applied to calculate the evaluation function recursively, and thus the heavy online computational burden could be solved. The FD for UAV pitot tube and elevator was taken as an example to demonstrate the effectiveness of the proposed method. The results showed that the faults of the UAV flight control system could be detected rapidly through the proposed approach

References

[1]  CORK L, WALKER R. Sensor fault detection for UAVs using a nonlinear dynamic model and the IMM-UKF algorithm[C] //Information, Decision and Control, 2007: 230-235.
[2]  WU C, QI J, SONG D, et al. Simultaneous state and parameter estimation based actuator fault detection and diagnosis for an unmanned helicopter[J]. International Journal of Applied Mathematics & Computer Science, 2015, 25(1):175-187.
[3]  LEE W H, KIM K H, CHAN G P, et al. Two-faults detection and isolation using extended parity space approach[J]. Journal of Electrical Engineering & Technology, 2012, 7(3):411-419.
[4]  DING S X, DING E L, JEINSCH T, et al. An approach to a unified design of FDI systems[C] // Proceedings of the 3rd Asian Control Conference. Shanghai, China:ASCC, 2000:2812-2817.
[5]  桂卫华, 彭涛, DING Steven X,等. 基于传感器最优配置的等价空间故障检测方法[J]. 控制与决策, 2007, 22(7):800-804. GUI Weihua, PENG Tao, DING Steven X, et al. Parity space approach to fault detection based on optimal sensor location[J]. Control and Decision, 2007, 22(7):800-804.
[6]  MAGRABI S M, GIBBENS P W. Decentralized fault detection and diagnosis in navigation systems for unmanned aerial vehicles[C] // Position Location and Navigation Symposium. San Diego, USA: IEEE, 2000: 363-370.
[7]  DING S X, JEINSCH T, DING E L. An approach to analysis and design of observer and parity space relation based FDI systems[C] // Proceedings of the 14th IFAC World Congress, Beijing, China:IFAC, 1999.
[8]  LIU X, GAO X, JIAN H. Robust unknown input observer based fault detection for high-order multi-agent systems with disturbances[J]. Isa Transactions, 2016, 61:15-28.
[9]  马岩, 曹金成, 黄勇,等. 基于BP神经网络的无人机故障诊断专家系统研究[J]. 长春理工大学学报(自然科学版), 2011, 34(4):137-139. MA Yan, CAO Jincheng, HUANG Yong, et al. A combined method based on expert system and BP neural network for UAV systems fault diagnosis[J]. Journal of Changchun University of Science and Technology(Natural Science Edition), 2011, 34(4):137-139.
[10]  SAMY I, POSTLETHWAITE I, GU D. Neural network based sensor validation scheme demonstrated on an unmanned air vehicle(UAV)model[C] //Proceedings of the 48th IEEE Conference on Decision and Control, CDC 2009. Shanghai, China:IEEE, 2009: 1237-1242.
[11]  刘晓东, 钟麦英, 柳海. 基于EKF的无人机飞行控制系统故障检测[J]. 上海交通大学学报, 2015, 49(6):884-888. LIU Xiaodong, ZHONG Maiying, LIU Hai. EKF-based fault detection of unmanned aerial vehicle flight control system[J]. Journal of Shanghai Jiao Tong University, 2015, 49(6):884-888.
[12]  QIAN M S, JIANG B, LIU H T. Dynamic surface active fault tolerant control design for the attitude control systems of UAV with actuator fault[J]. International Journal of Control Automation & Systems, 2016, 14(3):723-732.
[13]  HANSEN S, BLANKE M. Diagnosis of airspeed measurement faults for unmanned aerial vehicles[J]. IEEE Transactions on Aerospace & Electronic Systems, 2014, 50(1):224-239.
[14]  YANG Y, DING S X, LI L. Parameterization of nonlinear observer-based fault detection systems[J]. IEEE Transactions on Automatic Control, 2016, 61(11):3687-3692.
[15]  ZHAI S, WANG W, YE H. Fault diagnosis based on parameter estimation in closed-loop systems[J]. Control Theory & Applications Iet, 2015, 9(7):1146-1153.
[16]  BELLALI B, HAZZAB A, BOUSSERHANE I K, et al. Parameter estimation for fault diagnosis in nonlinear systems by ANFIS[J]. Procedia Engineering, 2016, 29(4):2016-2021.
[17]  ZHONG M, DING S X, HAN Q L, et al. Parity space-based fault estimation for linear discrete Time-Varying systems[J]. IEEE Transactions on Automatic Control, 2010, 55(7):1726-1731.
[18]  钟麦英, 薛婷. 基于观测器与小波变换的UAV作动器故障检测[J]. 系统仿真技术, 2016, 12(1):6-12. ZHONG Maiying, XUE Ting. Obeserver and wavelet transform based actuator fault detection for UAV[J]. System Simulation Technology, 2016, 12(1):6-12.
[19]  ZHONG M Y, ZHOU D H, DING S X. On H∞designing fault detection filter for linear discrete time-varying systems[J]. IEEE Transactions on Automatic Control, 2010, 55(7):1689-1695.
[20]  ZHONG M, SONG Y, DING S X. Parity space-based fault detection for linear discrete time-varying systems with unknown input[J]. Automatica, 2015, 59(1):120-126.
[21]  BATEMAN F, NOURA H, OULADSINE M. Fault diagnosis and fault-tolerant control strategy for the aerosonde UAV[J]. IEEE Transactions on Aerospace & Electronic Systems, 2011, 47(3):2119-2137.
[22]  KIM S H, NEGSH L, CHOI H L. Cubature Kalman filter based fault detection and isolation for formation control of multi-UAVs[J]. IFAC-Papers Online, 2016, 49(15):63-68.

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