留言板

尊敬的读者、作者、审稿人, 关于本刊的投稿、审稿、编辑和出版的任何问题, 您可以本页添加留言。我们将尽快给您答复。谢谢您的支持!

姓名
邮箱
手机号码
标题
留言内容
验证码

基于ASTSMO和UIO的故障估计方法

秦玉峰 史贤俊 翟禹尧 韩露 龙玉峰

秦玉峰, 史贤俊, 翟禹尧, 等 . 基于ASTSMO和UIO的故障估计方法[J]. 北京航空航天大学学报, 2020, 46(12): 2253-2263. doi: 10.13700/j.bh.1001-5965.2019.0631
引用本文: 秦玉峰, 史贤俊, 翟禹尧, 等 . 基于ASTSMO和UIO的故障估计方法[J]. 北京航空航天大学学报, 2020, 46(12): 2253-2263. doi: 10.13700/j.bh.1001-5965.2019.0631
QIN Yufeng, SHI Xianjun, ZHAI Yuyao, et al. Fault estimation method based on adaptive super-twisting sliding mode observer and unknown input observer[J]. Journal of Beijing University of Aeronautics and Astronautics, 2020, 46(12): 2253-2263. doi: 10.13700/j.bh.1001-5965.2019.0631(in Chinese)
Citation: QIN Yufeng, SHI Xianjun, ZHAI Yuyao, et al. Fault estimation method based on adaptive super-twisting sliding mode observer and unknown input observer[J]. Journal of Beijing University of Aeronautics and Astronautics, 2020, 46(12): 2253-2263. doi: 10.13700/j.bh.1001-5965.2019.0631(in Chinese)

基于ASTSMO和UIO的故障估计方法

doi: 10.13700/j.bh.1001-5965.2019.0631
详细信息
    作者简介:

    秦玉峰  男, 博士研究生。主要研究方向:飞行器检测与故障诊断技术

    史贤俊  男, 博士, 教授, 博士生导师。主要研究方向:飞行器测试性设计、故障检测与诊断

    翟禹尧  男, 博士研究生。主要研究方向:飞行器检测与故障诊断技术

    通讯作者:

    史贤俊, E-mail: sxjaa@sina.com

  • 中图分类号: TP273.2

Fault estimation method based on adaptive super-twisting sliding mode observer and unknown input observer

More Information
  • 摘要:

    针对系统在有未知干扰情况下的故障估计问题,提出一种基于自适应Super-Twisting滑模观测器(ASTSMO)和未知输入观测器(UIO)的故障估计方法。不需要已知故障导数的上界,避免了现有自适应算法存在的滑模增益过估计问题,并且能够处理多执行器同时发生故障的情况。首先,通过非奇异变换将原系统降阶为两个子系统,其中一个子系统只受故障的影响,另一个子系统同时含有故障和不确定干扰。对两个子系统分别设计ASTSMO观测器和UIO观测器,并对误差系统有限时间内收敛的条件进行了证明,同时给出了滑模增益初始值和时变增益的设计方法。然后,基于等效控制的概念对故障进行检测和估计。最后,通过仿真算例验证了所提故障估计方法的有效性。

     

  • 图 1  缓变故障的估计值与真实值

    Figure 1.  Estimated and true values of slow-varying fault

    图 2  发生缓变故障时的子系统1状态观测误差

    Figure 2.  State observation error of subsystem 1 when slow-varying fault occurs

    图 3  子系统2状态观测误差

    Figure 3.  State observation error of subsystem 2

    图 4  发生缓变故障时的k1自适应变化曲线

    Figure 4.  Adaptive change curves of k1 when slow-varying falut occurs

    图 5  发生缓变故障时的k2自适应变化曲线

    Figure 5.  Adaptive change curves of k2 when slow-varying falut occurs

    图 6  突变故障的估计值与真实值

    Figure 6.  Estimated and true values of sudden fault

    图 7  发生突变故障时的子系统1状态观测误差

    Figure 7.  State observation error of subsystem 1 when sudden fault occurs

    图 8  发生突变故障时的k1自适应变化曲线

    Figure 8.  Adaptive change curves of k1 when sudden fault occurs

    图 9  发生突变故障时的k2自适应变化曲线

    Figure 9.  Adaptive change curves of k2 when sudden fault occurs

    图 10  发生缓变故障时采用文献[15-18]方法的k1自适应变化曲线

    Figure 10.  Adaptive change curves of k1 of method in Refs.[15-18] when slow-varying fault occurs

    图 11  发生缓变故障时采用文献[15-18]方法的k2自适应变化曲线

    Figure 11.  Adaptive change curves of k2 of method in Refs.[15-18] when slow-varying fault occurs

    图 12  发生突变故障时采用文献[15-18]方法的k1自适应变化曲线

    Figure 12.  Adaptive change curves of k1 of method in Refs.[15-18] when sudden fault occurs

    图 13  发生突变故障时采用文献[15-18]方法的k2自适应变化曲线

    Figure 13.  Adaptive change curves of k2 of method in Refs.[15-18] when sudden fault occurs

    图 14  执行器同时发生故障时的故障估计结果

    Figure 14.  Fault estimations results for simultaneous actuator failures

    图 15  文献[21]方法的子系统1缓变故障状态观测误差

    Figure 15.  Subsystem 1 state observation error of method in Ref.[21] with slow-varying fault

    图 16  两种方法的缓变故障估计结果

    Figure 16.  Slow-varying fault estimation results of two methods

    图 17  文献[21]方法的子系统1突变故障状态观测误差

    Figure 17.  Subsystem 1 state observation error of method in Ref.[21] with sudden fault

    图 18  两种方法的突变故障估计结果

    Figure 18.  Sudden fault estimation results of two methods

  • [1] PATTON R J, JIE C.Robust model-based fault diagnosis for dynamic systems[M].Boston:Kluwer Academic Publishers, 1999:1-8.
    [2] TAN C P, EDWARDS C.Sliding mode observers for detection and reconstruction of sensor faults[J].Automatica, 2002, 38(10):1815-1821.
    [3] HE J, ZHANG C.Fault reconstruction based on sliding mode observer for nonlinear systems[J].Mathematical Problems in Engineering, 2012, 2012:1-22.
    [4] EDWARDS C, ALWI H, TAN C.Sliding mode methods for fault detection and fault tolerant control with application to aerospace systems[J].International Journal of Applied Mathematics and Computer Science, 2012, 22(1):109-124.
    [5] ALWI H, EDWARDS C, TAN C P.Sliding mode estimation schemes for incipient sensor faults[J].Automatica, 2009, 45(7):1679-1685.
    [6] WANG L, CAI M, ZHANG H, et al.Active fault-tolerant contr-ol for wind turbine with simultaneous actuator and sensor faults[J].Complexity, 2017, 2017:1-11.
    [7] BEN B A, DHAHRI S, BEN H F, et al.Simultaneous actuator and sensor faults reconstruction based on robust sliding mode observer for a class of nonlinear systems[J].Asian Journal of Control, 2017, 19(1):362-371.
    [8] HAMDI H, RODRIGUES M, MECHMECHE C, et al.Fault diagnosis based on sliding mode observer for LPV descriptor systems[J].Asian Journal of Control, 2019, 21(1):89-98.
    [9] GHOLAMI S, SAHA S, ALDEEN M.Fault tolerant control of electronically coupled distributed energy resources in microgrid systems[J].International Journal of Electrical Power and Energy Systems, 2018, 95:327-340.
    [10] 柳春, 姜斌, 张柯, 等.带扰动的线性系统微小故障早期诊断方法[J].上海交通大学学报, 2015, 49(6):889-896.

    LIU C, JIANG B, ZHANG K, et al.Incipient fault detection of linear system with disturbance[J].Journal of Shang Hai Jiao Tong University, 2015, 49(6):889-896(in Chinese).
    [11] RAOUFI R, MARQUEZ H J, ZINOBER A S I.H sliding mode observers for uncertain nonlinear lipschitz systems with fault estimation synthesis[J].International Journal of Robust and Nonlinear Control, 2010, 20(16):1785-1801.
    [12] 胡正高, 赵国荣, 黄婧丽, 等.基于二阶滑模观测器的连续系统故障估计[J].控制与决策, 2014, 29(12):2271-2276.

    HU Z G, ZHAO G R, HUANG J L, et al.Fault estimation of continuous-time systems based on second order sliding mode observation[J].Control and Decision, 2014, 29(12):2271-2276(in Chinese).
    [13] HUANGFU Y G, XU J, ZHAO D, et al.A novel battery state of charge estimation method based on a super-twisting sliding mode observer[J].Energies, 2018, 11(5):1211.
    [14] 陈诚, 韦常柱, 琚啸哲, 等.基于滑模观测补偿的四旋翼飞行器鲁棒动态逆控制[J].系统工程与电子技术, 2018, 40(1):119-126.

    CHEN C, WEI C Z, JU X Z, et al.Robust dynamic inversion control for quad-rotors unmanned vehicle based on sliding mode disturbance observation and compensation[J].System Engineering and Electronics, 2018, 40(1):119-126(in Chinese).
    [15] MOHAMED G, SOFIANE A A, NICOLAS L.Adaptive super twisting extended state observer based sliding mode control for diesel engine air path subject to matched and unmatched disturbance[J].Mathematics and Computers in Simulation, 2018, 151:111-130.
    [16] ZHANG M, GUAN Y, ZHAO W.Adaptive super-twisting sliding mode control for stabilization platform of laser seeker based on extended state observer[J].Optik, 2019, 199:163337.
    [17] HENDEL R, KHABER F, ESSOUNBOULI N.Adaptive high order sliding mode controller/observer based terminal sliding mode for MIMO uncertain nonlinear system[J/OL].International Journal of Control, 2019(2019-03-21)[2019-12-15].https://doi.org/10.1080/00207179.2019.1598580.
    [18] MALEKZADEH M, KARIMPOUR H.Adaptive super twisting vibration control of a flexible spacecraft with state rate estimation[J].Journal of Sound and Vibration, 2018, 422:300-317.
    [19] 杨雅君, 廖瑛, 尹大伟, 等.双层自适应快速super-twisting控制算法[J].控制理论与应用, 2016, 33(8):1119-1127.

    YANG Y J, LIAO Y, YIN D W, et al.Adaptive dual layer fast super twisting control algorithm[J].Control Theory & Applica-tions, 2016, 33(8):1119-1127(in Chinese).
    [20] HAUTUS M L J.Strong detectability and observers[J].Linear Algebra and its Applications, 1983, 50:353-368.
    [21] EDWARDS C, SHTESSEL Y.Adaptive dual-layer super-twisting control and observation[J].International Journal of Control, 2016, 89(9):1759-1766.
    [22] KHALIL H K.Nonlinear systems[M].Upper Saddle River:Prentice-Hall, 2002:323.
    [23] EDWARDS C, SPURGEON S K.On the development of discontinuous observers[J].International Journal of Control, 1994, 59(5):1211-1229.
  • 加载中
图(18)
计量
  • 文章访问数:  744
  • HTML全文浏览量:  135
  • PDF下载量:  76
  • 被引次数: 0
出版历程
  • 收稿日期:  2019-12-17
  • 录用日期:  2020-04-10
  • 网络出版日期:  2020-12-20

目录

    /

    返回文章
    返回
    常见问答