无人机高机动抗扰轨迹跟踪控制方法

王英勋; 宋欣屿; 赵江; 蔡志浩

doi:10.13700/j.bh.1001-5965.2022.0216

无人机高机动抗扰轨迹跟踪控制方法

doi: 10.13700/j.bh.1001-5965.2022.0216

北京航空航天大学自动化科学与电气工程学院, 北京 100083

详细信息

通讯作者:
蔡志浩, E-mail: czh@buaa.edu.cn

中图分类号: V249.1
计量
- 文章访问数: 608
- HTML全文浏览量: 158
- PDF下载量: 108
- 被引次数: 0
出版历程
- 收稿日期: 2022-04-02
- 录用日期: 2022-05-26
- 网络出版日期: 2022-06-14

Anti-disturbance trajectory tracking control method for aggressive quadrotors

School of Automation Science and Electrical Engineering, Beihang University, Beijing 100083, China

More Information

Corresponding author: CAI Zhihaoa, E-mail: czh@buaa.edu.cn

摘要

摘要:
针对传统的四旋翼控制方法在高机动飞行时控制效果不佳，难以跟踪机动性较强的轨迹且控制精度较低的问题，设计了基于增量非线性动态逆控制(INDI)方法和微分平坦前馈的轨迹跟踪控制器，不仅提高了高机动轨迹的跟踪精度，也增强了抗扰能力。由于角加速度无法直接获得，该方法对其非常敏感，设计了多种角加速度估计方法进行对比，通过飞行试验选择了效果最佳的互补滤波方法。试验结果证明：设计的基于互补滤波的前馈INDI方法可以控制飞行器快速、准确地跟踪高机动轨迹，且具有较强的抗扰能力。
- 四旋翼 /
- 轨迹跟踪 /
- 增量非线性动态逆控制(INDI) /
- 抗扰控制 /
- 角加速度估计
Abstract:
It is difficult for the traditional quadrotor control method with poor control effect in aggressive flight and low control accuracy to track trajectory with high speed and high acceleration. To solve this problem, a control method is proposed based on incremental nonlinear dynamic inversion(INDI) and differential flatness, as well as the complementary filter. The proposed control method not only improves the tracking accuracy of aggressive trajectories, but also enhances the anti-disturbance ability. Since the angular acceleration, which the proposed method is very sensitive to, cannot be directly obtained, a variety of angular acceleration estimation methods are designed for comparison, and the complementary filtering method with the best performance is selected through the flight test. The experimental results show that the proposed control method using INDI and differential flatness based on complementary filter can control the quadrotor to track aggressive trajectories quickly and accurately, and has strong anti-interference ability.
- quadrotor /
- trajectory tracking /
- incremental nonlinear dynamic inversion (INDI) /
- disturbance rejection control /
- angular acceleration estimation

HTML全文

图 1 四旋翼及机体坐标系定义

Figure 1. Quadrotor with body-fixed reference system

下载: 全尺寸图片幻灯片

图 2 旋翼序号及旋转方向

Figure 2. Rotor serial number and rotation direction

下载: 全尺寸图片幻灯片

图 3 总体控制框图

Figure 3. Overall control diagram

下载: 全尺寸图片幻灯片

图 4 位置和速度控制

Figure 4. Position and velocity control

下载: 全尺寸图片幻灯片

图 5 姿态和角速度控制

Figure 5. Attitude and angular rate control

下载: 全尺寸图片幻灯片

图 6 互补滤波

Figure 6. Complementary filter

下载: 全尺寸图片幻灯片

图 7 角加速度估计结果

Figure 7. Angular acceleration estimation results

下载: 全尺寸图片幻灯片

图 8 低速轨迹跟踪曲线

Figure 8. Low speed trajectory tracking curves

下载: 全尺寸图片幻灯片

图 9 中速轨迹跟踪曲线

Figure 9. Medium speed trajectory tracking curves

下载: 全尺寸图片幻灯片

图 10 高机动轨迹跟踪曲线

Figure 10. Aggressive trajectory tracking curves

下载: 全尺寸图片幻灯片

图 11 高机动轨迹跟踪曲线

Figure 11. Aggressive trajectory tracking curves

下载: 全尺寸图片幻灯片

图 12 悬挂纸板的四旋翼无人机

Figure 12. Quadrotor with cardboard drag plate

下载: 全尺寸图片幻灯片

图 13 带纸板轨迹跟踪曲线

Figure 13. Tajectory tracking curves with cardboard drag plate

下载: 全尺寸图片幻灯片

图 14 带纸板轨迹跟踪曲线

Figure 14. Trajectory tracking curves with cardboard drag plate

下载: 全尺寸图片幻灯片

图 15 悬停抗扰试验

Figure 15. Hover test with disturbance

下载: 全尺寸图片幻灯片

图 16 悬停抗扰曲线

Figure 16. Curves for hover with disturbance

下载: 全尺寸图片幻灯片

表 1 低速轨迹跟踪效果

Table 1. Low speed trajectory tracking performance

参数	前馈PID方法	前馈INDI方法
位置均方根误差/cm	8.091	4.232
偏航角均方根误差/(°)	2.735	0.433
最大速度/(m·s^-1)	3.769	4.116
平均速度/(m·s^-1)	1.944	2.086
最大加速度/(m·s^-2)	8.855	9.192
平均加速度/(m·s^-2)	3.864	4.122

下载: 导出CSV

表 2 中速轨迹跟踪效果

Table 2. Medium speed trajectory tracking performance

参数	前馈PID方法	前馈INDI方法
位置均方根误差/cm	17.24	6.021
偏航角均方根误差/(°)	2.042	1.972
最大速度/(m·s^-1)	6.233 1	6.425
平均速度/(m·s^-1)	2.414 8	2.601
最大加速度/(m·s^-2)	16.097 5	13.839
平均加速度/(m·s^-2)	5.299 5	4.919

下载: 导出CSV

表 3 高机动轨迹跟踪效果

Table 3. Aggressive trajectory tracking performance

参数	LPF	KF	CF
位置均方根误差/cm	15.072	14.084	10.310
偏航角均方根误差/(°)	4.751	4.298	1.552
平均速度/(m·s^-1)	4.654	4.643	4.654
最大速度/(m·s^-1)	10.815	10.922	10.416
平均加速度/(m·s^-2)	7.604	7.555	7.434
最大加速度/(m·s^-2)	18.510	17.239	17.119

下载: 导出CSV

表 4 轨迹跟踪效果

Table 4. Trajectory tracking performance

参数	前馈INDI方法(不带纸板)	前馈INDI方法(带纸板)	前馈PID方法(不带纸板)	前馈PID方法(带纸板)
位置均方根误差/cm	4.232	4.494	8.091	10.00
偏航角均方根误差/(°)	0.433	0.460	2.735	6.592
最大速度/(m·s^-1)	4.116	4.034	3.769	3.283
平均速度/(m·s^-1)	2.086	2.081	1.944	1.950
最大加速度/(m·s^-2)	9.192	9.299	8.855	10.147
平均加速度/(m·s^-2)	4.122	4.096	3.864	4.078

下载: 导出CSV

表 5 悬停抗扰效果

Table 5. Performance for hover with disturbance

参数	前馈INDI方法	前馈PID方法
位置均方根误差/cm	1.199	12.273
位置最大误差/cm	4.502	47.670
偏航角均方根误差/(°)	0.018 9	0.059 6
偏航角最大误差/(°)	0.081 9	0.269

下载: 导出CSV

参考文献(27)

[1]	ROOT P. Fast lightweight autonomy (FLA) (Archived)[EB/OL]. (2020-04-08)[2022-04-01].
[2]	吕震华, 高亢. 美国无人集群城市作战应用发展综述[J]. 中国电子科学研究院学报, 2020, 15(8): 738-745. LV Z H, GAO K. Review of the development of drone swarm urban combat applications in the USA[J]. Journal of CAEIT, 2020, 15(8): 738-745(in Chinese).
[3]	BYRNES C I, ISIDORI A. Nonlinear control systems[J]. Lecture Notes in Control and Information Sciences, 2003, 242(65): 408.
[4]	SNELL S A, NNS D F, ARRARD W L. Nonlinear inversion flight control for a supermaneuverable aircraft[J]. Guidance, 2015, 15(4): 976-984.
[5]	LEE D, KIM H J, SASTRY S. Feedback linearization vs. adaptive sliding mode control for a quadrotor helicopter[J]. International Journal of Control Automation and Systems, 2009, 7(3): 419-428.
[6]	SIEBERLING S, CHU Q P, MULDER J A. Robust flight control using incremental nonlinear dynamic inversion and angular acceleration prediction[J]. Journal of Guidance, Control, and Dynamics, 2010, 33(6): 1732-1742.
[7]	SIMPLÍCIO P, PAVEL M D, VAN KAMPEN E, et al. An acceleration measurements-based approach for helicopter nonlinear flight control using incremental nonlinear dynamic inversion[J]. Control Engineering Practice, 2013, 21(8): 1065-1077.
[8]	LU P, VAN KAMPEN E J, DE VISSER C, et al. Aircraft fault-tolerant trajectory control using incremental nonlinear dynamic inversion aircraft fault-tolerant trajectory control using incremental nonlinear dynamic inversion[J]. Control Engineering Practice, 2016, 57: 126-141.
[9]	SMEUR E J, CHU Q P, CROON G. Adaptive incremental nonlinear dynamic inversion for attitude control of micro aerial vehicles: AIAA 2016-1390[R]. Reston: AIAA, 2016.
[10]	SMEUR E J J, DE CROON G C H E, CHU Q. Cascaded incremental nonlinear dynamic inversion for MAV disturbance rejection[J]. Control Engineering Practice, 2018, 73: 79-90.
[11]	TAL E, KARAMAN S. Accurate tracking of aggressive quadrotor trajectories using incremental nonlinear dynamic inversion and differential flatness[J]. IEEE Transactions on Control Systems Technology, 2021, 29(3): 1203-1218.
[12]	ZHAO K, ZHANG J, MA D, et al. Composite disturbance rejection attitude control for quadrotor with unknown disturbance[J]. IEEE Transactions on Industrial Electronics, 2020, 67(8): 6894-6903.
[13]	WANG Z, ZHAO J, CAI Z, et al. Onboard actuator model-based incremental nonlinear dynamic inversion for quadrotor attitude control: Method and application[J]. Chinese Journal of Aeronautics, 2021, 34(11): 216-227.
[14]	JI C H, KIM C S, KIM B S. A hybrid incremental nonlinear dynamic inversion control for improving flying qualities of asymmetric store configuration aircraft[J]. Aerospace, 2021, 8(5): 23.
[15]	CHEN G, LIU A, HU J, et al. Attitude and altitude control of unmanned aerial-underwater vehicle based on incremental nonlinear dynamic inversion[J]. IEEE Access, 2020, 8: 156129-156138.
[16]	OVASKA S J, VALIVⅡTA S. Angular acceleration measurement: A review[J]. IEEE Transactions on Instrumentation and Measurement, 1998, 47(5): 1211-1217.
[17]	BUBNOV A V, EMASHOV V A, CHUDINOV A N, et al. Measurement methods for angular acceleration and errors for angular velocity of synchrophase electric drive[J]. Measurement Techniques, 2014, 57(8): 860-865.
[18]	CHENG S, FU M, WANG M, et al. Modeling for fluid transients in liquid-circular angular accelerometer[J]. IEEE Sensors Journal, 2017, 17(2): 267-273.
[19]	MOKHTARI E, ELHABIBY M, SIDERIS M G. Wavelet spectral techniques for error mitigation in the superconductive angular accelerometer output of a gravity gradiometer system[J]. IEEE Sensors Journal, 2017, 17(12): 3782-3793.
[20]	ALROWAIS H, GETZ P, KIM M G, et al. Bio-inspired fluidic thermal angular accelerometer[C]//IEEE International Conference on Micro Electro Mechanical Systems. Piscataway: IEEE Press, 2016: 15821613.
[21]	COSTELLO M, JITPRAPHAI T. Determining angular velocity and angular acceleration of projectiles using triaxial acceleration measurements[J]. Journal of Spacecraft and Rockets, 2002, 39(1): 73-80.
[22]	VALIVⅡTA S, OVASKA S J. Delayless acceleration measurement method for elevator control[J]. IEEE Transactions on Industrial Electronics, 1998, 45(2): 364-366.
[23]	CHOUKROUN D, BAR-ITZHACK I Y, OSHMAN Y. Novel quaternion Kalman filter[J]. IEEE Transactions on Aerospace and Electronic Systems, 2006, 42(1): 174-190.
[24]	VALENTI R G, DRYANOVSKI I, XIAO J. A linear Kalman filter for MARG orientation estimation using the algebraic quaternion algorithm[J]. IEEE Transactions on Instrumentation and Measurement, 2016, 65(2): 467-481.
[25]	BELANGER P R, DOBROVOLNY P, HELMY A, et al. Estimation of angular velocity and acceleration from shaft encoder measurements[J]. International Journal of Robotics Research, 2002, 17(11): 1225-1233.
[26]	HAN J D, HE Y Q, XU W L. Angular acceleration estimation and feedback control: An experimental investigation[J]. Mechatronics, 2007, 17(9): 524-532.
[27]	MELLINGER D, KUMAR V. Minimum snap trajectory generation and control for quadrotors[C]//IEEE International Conference on Robotics and Automation. Piscataway: IEEE Press, 2011: 2520-2525.