2.845

2023影响因子

(CJCR)

  • 中文核心
  • EI
  • 中国科技核心
  • Scopus
  • CSCD
  • 英国科学文摘

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

基于非线性干扰观测器的飞机全电刹车系统滑模控制设计

李繁飙 黄培铭 阳春华 廖力清 桂卫华

李繁飙, 黄培铭, 阳春华, 廖力清, 桂卫华. 基于非线性干扰观测器的飞机全电刹车系统滑模控制设计. 自动化学报, 2021, 47(11): 2557−2569 doi: 10.16383/j.aas.c201041
引用本文: 李繁飙, 黄培铭, 阳春华, 廖力清, 桂卫华. 基于非线性干扰观测器的飞机全电刹车系统滑模控制设计. 自动化学报, 2021, 47(11): 2557−2569 doi: 10.16383/j.aas.c201041
Li Fan-Biao, Huang Pei-Ming, Yang Chun-Hua, Liao Li-Qing, Gui Wei-Hua. Sliding mode control design of aircraft electric brake system based on nonlinear disturbance observer. Acta Automatica Sinica, 2021, 47(11): 2557−2569 doi: 10.16383/j.aas.c201041
Citation: Li Fan-Biao, Huang Pei-Ming, Yang Chun-Hua, Liao Li-Qing, Gui Wei-Hua. Sliding mode control design of aircraft electric brake system based on nonlinear disturbance observer. Acta Automatica Sinica, 2021, 47(11): 2557−2569 doi: 10.16383/j.aas.c201041

基于非线性干扰观测器的飞机全电刹车系统滑模控制设计

doi: 10.16383/j.aas.c201041
基金项目: 国家自然科学基金(61973319), 湖南省优秀青年基金(2019JJ30032), 机器人技术与系统国家重点实验室开放基金(SKLRS-2020-KF-14)资助
详细信息
    作者简介:

    李繁飙:中南大学自动化学院教授. 2015年获得哈尔滨工业大学控制科学与工程博士学位. 主要研究方向为复杂工业过程智能控制与优化, 非连续控制理论. E-mail: fanbiaoli@csu.edu.cn

    黄培铭:中南大学自动化学院硕士研究生. 主要研究方向为飞机刹车系统建模与控制. E-mail: peiming_huang@csu.edu.cn

    阳春华:中南大学自动化学院教授. 2002年获得中南大学博士学位. 主要研究方向为复杂工业过程建模与优化, 故障诊断和智能系统. E-mail: ychh@csu.edu.cn

    廖力清:中南大学自动化学院教授. 2010年获得中南大学博士学位. 主要研究方向为电力电子与电力传动, 电力系统自动化, 飞机起飞着陆系统智能控制. 本文通信作者. E-mail: zdh-dqkz@csu.edu.cn

    桂卫华:中国工程院院士, 中南大学自动化学院教授. 1981年获得中南矿冶学院硕士学位. 主要研究方向为复杂工业过程建模, 优化与控制应用, 故障诊断与分布式鲁棒控制. E-mail: gwh@csu.edu.cn

Sliding Mode Control Design of Aircraft Electric Brake System Based on Nonlinear Disturbance Observer

Funds: Supported by National Natural Science Foundation of China (61973319), Excellent Youth Natural Science Foundation of Hunan Province (2019JJ30032), State Key Laboratory of Robotics and Systems (HIT) (SKLRS-2020-KF-14)
More Information
    Author Bio:

    LI Fan-Biao Professor at the School of Automation, Central South University. He received his Ph. D. degree from Harbin Institute of Technology in 2015. His research interest covers intelligent control and optimization of complex industrial processes, discontinuous control theory

    HUANG Pei-Ming Master student at the School of Automation, Central South University. His research interest covers aircraft braking system modeling and control

    YANG Chun-Hua Professor at the School of Automation, Central South University. She received her Ph. D. degree from Central South University in 2002. Her research interest covers complex industrial process modeling and optimization, fault diagnosis, and intelligent system

    LIAO Li-Qing Professor at the School of Automation, Central South University. He received his Ph. D. degree from Central South University in 2010. His research interest covers power electronics and power transmission, power system automation, and intelligent control of aircraft take-off and landing system. Corresponding author of this paper

    GUI Wei-Hua Academician of the Chinese Academy of Engineering, and professor at the School of Automation, Central South University. He received his master degree from Central South Institute of Mining and Metallurgy in 1981. His research interest covers complex industrial process modeling, optimization and control applications, fault diagnosis and distribute robust control

  • 摘要: 飞机防滑刹车具有典型的强非线性、强耦合和参数时变等特点, 并且跑道环境的干扰容易对飞机的地面滑跑性能造成不利影响. 本文提出了一种基于非线性干扰观测器的飞机全电防滑刹车系统滑模控制设计方法. 首先, 考虑了实际刹车不确定性干扰条件下的防滑刹车动力学建模问题, 通过对高阶非线性刹车系统进行反馈线性化处理, 简化了基于严格反馈的模型. 其次, 基于对主轮打滑原因的深入分析, 设计了非线性干扰观测器对干扰进行在线估计, 并在控制律设计中引入补偿部分. 通过构造递归结构的快速终端滑模控制器来跟踪实时变化的最佳滑移率并建立稳定性条件, 实现了飞机全电防滑刹车系统的有限时间快速稳定并有效抑制了主轮锁定打滑. 通过在不同跑道状态下进行模拟仿真, 验证了本文提出的飞机防滑刹车控制策略可以有效地提高刹车效率.
  • 图  1  飞机机体受力图

    Fig.  1  Force diagram of aircraft fuselage

    图  2  单个主轮受力分析图

    Fig.  2  Force analysis diagram of single main wheel

    图  3  干沥青跑道摩擦系数模型曲线

    Fig.  3  Curve of friction coefficient model on dry asphalt runway

    图  4  ${v_x}$ = 30 m/s不同跑道状态$\mu $-$\lambda $曲线

    Fig.  4  Curve of $\mu $-$\lambda $ on the different runway conditions with ${v_x}$= 30 m/s

    图  5  $\lambda $$\mu $关系曲线

    Fig.  5  Relational between $\lambda $ and $\mu $

    图  6  飞机防滑刹车闭环控制总框图

    Fig.  6  General block diagram of aircraft antiskid brake closed-loop control

    图  7  干扰观测仿真结果

    Fig.  7  Simulation results of disturbance observation

    图  8  干沥青跑道状态下两种控制方法的飞机防滑刹车控制仿真结果

    Fig.  8  Simulation results of aircraft antiskid brake control with two control methods under dry asphalt runway condition

    图  9  雪跑道状态下飞机防滑刹车控制仿真结果

    Fig.  9  Simulation results of aircraft antiskid brake control under snow runway condition

    表  1  飞机防滑刹车系统参数

    Table  1  Parameters of antiskid braking system

    参数具体描述
    $m$飞机质量
    ${v_x}$飞机纵向滑跑速度
    ${F_x}$迎风阻力
    ${F_y}$飞机升力
    ${F_{f1}}$单个主轮与地面间摩擦力
    ${F_{f2}}$单个前轮与地面间摩擦力
    ${n_1}$受刹主轮个数
    ${n_2}$前轮个数
    ${T_v}$发动机推力
    ${N_1}$单个主轮垂直载荷
    ${N_2}$单个前轮垂直载荷
    $g$重力加速度
    $a$前轮中心与飞机重心的水平距离
    $b$主轮中心与飞机重心的水平距离
    $h$飞机重心与地面的垂直高度
    ${h_t}$发动机推力点与飞机重心的垂直高度
    ${T_{{\rm{int}} }}$发动机剩余推力
    ${k_x}$纵向空气阻力系数
    ${k_y}$横向空气阻力系数
    $\rho $空气密度
    ${C_d}$飞机气动阻力系数
    ${C_L}$飞机滑跑时的升力系数
    ${S_w}$机翼总面积
    下载: 导出CSV

    表  2  摩擦系数模型参数

    Table  2  Parameters of friction coefficient model

    跑道状态${c_1}$${c_2}$${c_3}$${c_4}$
    干沥青1.280123.990.520.04
    干混凝土1.197325.1680.53730.04
    湿沥青0.85733.8220.3470.04
    0.194694.1290.06460.04
    0.05306.3900.04
    下载: 导出CSV

    表  3  飞机防滑刹车性能指标

    Table  3  Aircraft antiskid brake performance index

    性能指标干沥青
    刹车距离 (m)496.8072060.411
    刹车时间 (s)11.8253.92
    跟踪效率 (%)99.4398.95
    制动效率 (%)99.6699.17
    下载: 导出CSV

    表  4  两种控制方法性能对比

    Table  4  Performance comparison of the two control methods

    对比项目递归型传统型
    机轮仅工作在稳定区
    最佳滑移率和最大摩擦系数的稳态误差
    暂态至稳态的快速性较快较慢
    鲁棒性较强较弱
    下载: 导出CSV
  • [1] Huang C, Jiao Z-X, Shang Y-X, Yao J-Y. Antiskid braking control with on/off valves for aircraft applications. Journal of Aircraft, 2013, 50(6): 1869-1879 doi: 10.2514/1.C032242
    [2] Kebairi A, Becherif M, Bagdouri M E. Modelling, simulation and identification of an engine air path electromechanical actuator. Control Engineering Practice, 2015, 34: 88-97 doi: 10.1016/j.conengprac.2014.07.009
    [3] Yin Q-Z, Wei X-H, Nie H, Deng J. Study on modal characteristics and vibration reduction of an aircraft rotor-stator brake-induced squeal system. Acta Mechanica Sinica, 2020, 36(6): 1350-1359 doi: 10.1007/s10409-020-01003-9
    [4] Dai Y-Q, Yu L-Y, Song J, Abi L, Zheng S. Aircraft ground braking assistant control based on pilot control model. IEEE Access, 2020, 8: 88643-88650 doi: 10.1109/ACCESS.2020.2993173
    [5] Yazici H, Sever M. Observer based optimal vibration control of a full aircraft system having active landing gears and biodynamic pilot model. Shock and Vibration, 2016, 7: 1-20
    [6] Jiao Z-X, Sun D, Shang Y-X, Liu X-C, Wu S. A high efficiency aircraft anti-skid brake control with runway identification. Aerospace Science and Technology, 2019, 91: 82-95 doi: 10.1016/j.ast.2019.05.001
    [7] Jiao Z-X, Zhang H, Shang Y-X, Liu X-C, Wu S. A power-by-wire aircraft brake system based on high-speed on-off valves. Aerospace ence and Technology, 2020, 106: 106177 doi: 10.1016/j.ast.2020.106177
    [8] Han K, Lee B, Choi S. Development of an antilock brake system for electric vehicles without wheel slip and road friction information. IEEE Transactions on Vehicular Technology, 2019, 68(6): 5506-5517 doi: 10.1109/TVT.2019.2911687
    [9] Liang B, Zhu Y-Q, Li Y-R, He P-J, Li W-L. Adaptive nonsingular fast terminal sliding mode control for braking systems with electro-mechanical actuators based on radial basis function. Energies, 2017, 10(10): 1637 doi: 10.3390/en10101637
    [10] Zhang X, Lin H. Backstepping adaptive neural network control for electric braking systems of aircrafts. Algorithms, 2019, 12(10): 215 doi: 10.3390/a12100215
    [11] Zhang Z H, Li Y R. Modeling and simulation of switched reluctance machine based aircraft electric brake system by BP neural network. In: Proceedings of the 9th IEEE Conference on Industrial Electronics and Applications (ICIEA). Hangzhou China: IEEE, 2014. 338−341
    [12] Jiao Z-X, Bai N, Sun D, Liu X-C, Wu S. A novel aircraft brake disturbance recognition model. Aerospace Science and Technology, 2020, 107(2): 106337
    [13] Peng Z-H, Jiang Y, Wang J. Event-triggered dynamic surface control of an underactuated autonomous surface vehicle for target Enclosing. IEEE Transactions on Industrial Electronics, 2021, 68(4): 3402-3412 doi: 10.1109/TIE.2020.2978713
    [14] 于欣波, 贺威, 薛程谦, 孙永坤, 孙长银. 基于扰动观测器的机器人自适应神经网络跟踪控制研究. 自动化学报, 2019, 45(07): 1307-1324

    Yu Xin-Bo, He Wei, Xue Cheng-Qian, Sun Yong-Kun, Sun Chang-Yin. Disturbance observer-based adaptive neural network tracking control for robots. Acta Automatica Sinica, 2019, 45(07): 1307-1324
    [15] 李杰, 齐晓慧, 夏元清, 高志强. 线性/非线性自抗扰切换控制方法研究. 自动化学报, 2016, 42(02): 202-212

    Li Jie, Qi Xiao-Hui, Xia Yuan-Qing, Gao Zhi-Qiang. On linear/nonlinear active disturbance rejection switching control, Acta Automatica Sinica, 2016, 42(02): 202-212
    [16] Wang L-J, Li H-Y, Zhou Q, Lu R-Q. Adaptive fuzzy control for nonstrict feedback systems with unmodeled dynamics and fuzzy dead zone via output feedback. IEEE Transactions on Cybernetics, 2017, 47(9): 2400-2412 doi: 10.1109/TCYB.2017.2684131
    [17] 王东委, 富月. 基于高阶观测器和干扰补偿控制的模型预测控制方法. 自动化学报, 2020, 46(06): 1220-1228

    Wang Dong-Wei, Fu Yue. Model predict control method based on higher-order observer and disturbance compensation control, Acta Automatica Sinica, 2020, 46(06): 1220-1228
    [18] Li F-B, Du C-L, Yang C-H, Gui W-H. Passivity-based asynchronous sliding mode control for delayed singular Markovian jump systems. IEEE Transactions on Automatic Control, 2017, 63(8): 2715-2721
    [19] Dinçmen E, Güvenç B A, Acarman T. Extremum-seeking control of ABS braking in road vehicles with lateral force improvement. IEEE Transactions on Control Systems Technology, 2012, 22(1): 230-237
    [20] Jiao Z-X, Liu X-C, Shang Y-X, Huang C. An integrated self-energized brake system for aircrafts based on a switching valve control. Aerospace Science and Technology, 2017, 60: 20-30 doi: 10.1016/j.ast.2016.10.021
    [21] Chen M-Q, Liu W-S, Ma Y-Z, Wang J, Xu F-R, Wang Y-J. Mixed slip-deceleration PID control of aircraft wheel braking system. IFAC-PapersOnLine, 2018, 51(4): 160-165 doi: 10.1016/j.ifacol.2018.06.059
    [22] Qiu Y-N, Liang X-G, Dai Z-Y. Backstepping dynamic surface control for an anti-skid braking system. Control Engineering Practice, 2015, 42: 140-152 doi: 10.1016/j.conengprac.2015.05.013
    [23] Sun D, Jiao Z-X, Shang Y-X, Wu S, Liu X-C. High-efficiency aircraft antiskid brake control algorithm via runway condition identification based on an on-off valve array. Chinese Journal of Aeronautics, 2019, 32(11): 2538-2556 doi: 10.1016/j.cja.2019.08.020
    [24] 李丰羽, 焦宗夏. 基于结合力模型的自适应飞机防滑刹车控制. 北京航空航天大学学报, 2013, 39(04): 447-452

    Li Feng-Yu, Jiao Zong-Xia. Adaptive control for aircraft antiskid braking system based on friction force model. Journal of Beijing University of Aeronautics and Astronautics, 2013, 39(04): 447-452
    [25] Chen M-Q, Xu F-R, Liang X-L, Liu W-S. MSD-based NMPC aircraft anti-skid brake control method considering runway variation. IEEE Access, 2021, 9: 51793-51804 doi: 10.1109/ACCESS.2021.3070066
    [26] Liu C, Liu G, Fang J-C. Feedback linearization and extended state observer-based control for rotor-AMBs system with mismatched uncertainties. IEEE Transactions on Industrial Electronics, 2016, 64(2): 1313-1322
    [27] Wu Y-Q, Isidori A, Lu R-Q, Khalil H K. Performance recovery of dynamic feedback-linearization methods for multivariable nonlinear systems. IEEE Transactions on Automatic Control, 2020, 65(4): 1365-1380 doi: 10.1109/TAC.2019.2924176
    [28] Ginoya D, Shendge P D, Phadke S B. Sliding mode control for mismatched uncertain systems using an extended disturbance observer. IEEE Transactions on Industrial Electronics, 2013, 61(4): 1983-1992
    [29] Bhat S P, Bernstein D S. Finite-time stability of continuous autonomous systems. SIAM Journal on Control and Optimization, 2000, 38(3): 751-766 doi: 10.1137/S0363012997321358
    [30] Zhou H-B, Song S-M, Song J-H. Design of sliding mode guidance law with dynamic delay and impact angle constraint. International Journal of Control, Automation and Systems, 2017, 15(1): 239-247 doi: 10.1007/s12555-015-0186-9
    [31] Hu Y-H, Wang H, He S, Zheng J-C, Ping Z-W, Shao K, Cao Z-W, Man Z-H. Adaptive tracking control of an electronic throttle valve based on recursive terminal sliding mode. IEEE Transactions on Vehicular Technology, 2020, 1(1): 1-11
    [32] Chen X-L, Dai Z-Y, Lin H, Qiu Y-N, Liang X-G. Asymmetric barrier Lyapunov function-based wheel slip control for antilock braking system. International Journal of Aerospace Engineering, 2015, 2015: 1-10
  • 加载中
图(10) / 表(4)
计量
  • 文章访问数:  2202
  • HTML全文浏览量:  549
  • PDF下载量:  560
  • 被引次数: 0
出版历程
  • 收稿日期:  2020-12-18
  • 网络出版日期:  2021-06-28
  • 刊出日期:  2021-11-18

目录

    /

    返回文章
    返回