基于模型预测控制的子母式无人机编队飞行控制方法

李云鹏; 张立宪; 韩岳江; 蔡博; 张宇轩; 肖广洲

doi:10.16383/j.aas.c240405

基于模型预测控制的子母式无人机编队飞行控制方法

doi: 10.16383/j.aas.c240405 cstr: 32138.14.j.aas.c240405

1.
哈尔滨工业大学航天学院哈尔滨 150001

基金项目: 国家自然科学基金(62225305, 12072088), 中央高校基本科研业务费专项基金 (HIT.OCEF.2022047, HIT.BRET.2022004, HITDZIJ.2023049), 基础科研项目(2022603C016), 机器人与系统国家重点实验室(HIT), 黑龙江头雁团队资助

详细信息

作者简介:
李云鹏：哈尔滨工业大学航天学院博士研究生. 主要研究方向为无人机路径规划与跟踪控制技术. E-mail: yunpengli@hit.edu.cn

张立宪：哈尔滨工业大学航天学院教授. 主要研究方向为不确定性切换系统, 模型预测控制及其在多模态无人系统中的应用. 本文通信作者. E-mail: lixianzhang@hit.edu.cn

韩岳江：哈尔滨工业大学航天学院博士研究生. 主要研究方向为混杂切换控制, 模型预测控制. E-mail: hanyuejiang@hit.edu.cn

蔡博：哈尔滨工业大学航天学院副教授. 主要研究方向为多模态无人系统控制, 随机切换系统控制. E-mail: bcai@hit.edu.cn

张宇轩：哈尔滨工业大学航天学院硕士研究生. 主要研究方向为固定翼无人机的规划与控制. E-mail: yxzhang@stu.hit.edu.cn

肖广洲：哈尔滨工业大学航天学院博士研究生. 主要研究方向为机器人路径规划及优化, 机器人轨迹规划. E-mail: guangzhouxiao@hit.edu.cn

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出版历程
- 收稿日期: 2024-06-28
- 录用日期: 2024-10-09
- 网络出版日期: 2025-01-04

Model Predictive Control-based Formation Flight Control Method for Composite UAVs

1.
School of Astronautics, Harbin Institute of Technology, Harbin 150001

Funds: Supported by National Natural Science Foundation of China (62225305, 12072088), the Fundamental Research Funds for the Central Universities, China (HIT.OCEF.2022047, HIT.BRET.2022004, HITDZIJ.2023049), the Basic Research Project (2022603C016), State Key Laboratory of Robotics and System (HIT), and the Heilongjiang Touyan Team

More Information

Author Bio:
LI Yun-Peng　Ph.D. candidate at the School of Astronautics, Harbin Institute of Technology. His research interest covers path planning and trajectory tracking control of unmanned aerial vehicles

ZHANG Li-Xian　Professor at the School of Astronautics, Harbin Institute of Technology. His research interest covers nondeterministic switched systems, model predictive control, and their applications in multimodal unmanned systems. Corresponding author of this paper

HAN Yue-Jiang　Ph.D. candidate at the School of Astronautics, Harbin Institute of Technology. His research interest covers hybird switched control and model predictive control

CAI Bo　Associate professor at the School of Astronautics, Harbin Institute of Technology. His research interest covers multimodal unmanned system control, and stochastic switched system control

ZHANG Yu-Xuan　Master student at the School of Astronautics, Harbin Institute of Technology. His research interest covers planning and control of fixed-wing unmanned aerial vehicles

XIAO Guang-Zhou　Ph.D. candidate at the School of Astronautics, Harbin Institute of Technology. His research interest covers path planning, path optimization, trajectory planning, and their applications in robotics

摘要

摘要: 子母式无人机(Unmanned aerial vehicles, UAVs)通常指一类由无人载机搭载和投放多架子机执行协同作业任务的新型飞行器. 相较于传统无人机和无人机集群, 子母式无人机兼具航程长、空间可达性强等优势, 得到了广泛关注. 首先针对子母式无人机在编队飞行任务中的载机姿态稳定控制与子机轨迹跟踪控制问题, 建立子母式无人机动力学模型. 在此基础上, 分别设计基于多平衡点切换模型预测控制的飞行控制方法以及基于多胞不确定性模型预测控制的轨迹跟踪控制方法, 实现了子母式无人机的稳定、安全编队飞行. 仿真结果表明, 所提出的方法能够实现预期的编队飞行目标, 具有良好的稳定性和鲁棒性.
- 子母式无人机 /
- 模型预测控制 /
- 切换控制 /
- 编队控制
Abstract: Composite unmanned aerial vehicles (UAVs) typically refer to a class of novel aircraft, each of which involves a carrier UAV deploying and airdropping multiple parasite UAVs for collaborative operations. Compared to traditional UAVs and UAV swarms, composite UAVs offer significant advantages in terms of extended range and enhanced spatial accessibility, garnering widespread attention. First, the dynamic model of the composite UAV is established for the problem of attitude stabilization control for the carrier UAV and trajectory tracking control for the parasite UAVs during formation flight tasks. On this basis, the flight control method based on multi-equilibrium switched model predictive control, as well as the trajectory tracking control method based on model predictive control with the polytopic model uncertainty, are designed to achieve a stable and safe formation flight of the composite UAV. Simulation results indicate that the proposed methods achieve the anticipated formation flight, demonstrating satisfying stability and robustness.
- Composite unmanned aerial vehicles (UAVs) /
- model predictive control /
- switched control /
- formation control

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图 1 子机挂载状态下的子母式无人机

Fig. 1 A composite UAV with the parasite UAVs loaded

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图 2 子母式无人机坐标系示意图

Fig. 2 Illustration of the coordinate frames of the composite UAV

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图 3 多平衡点切换系统状态轨迹及区域稳定性示意图

Fig. 3 Illustration of state trajectory and region stability for a multi-equilibrium switched system

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图 4 子机投放后的升阻比

Fig. 4 Lift-drag ratio of the parasite UAVs aftering dropping

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图 5 子母式无人机飞行轨迹

Fig. 5 Flight trajectories of the composite UAV

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图 6 子母式无人机飞行状态

Fig. 6 Flight states of the composite UAV

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图 7 载机控制量

Fig. 7 Control inputs of the carrier UAV

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图 8 子机控制量

Fig. 8 Control inputs of the parasite UAVs

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表 1 不同模态下载机飞行状态及平衡点

Table 1 Flight states and equilibria of the carrier UAV in different modes

模态	I	II	III	IV	V
时间	0 ~ 5 s	5 ~ 10 s	10 ~ 25.7 s	25.7 ~ 30.7 s	30.7 ~ 40 s
子机1	$ \surd $
子机2	$ \surd $	$ \surd $	$ \surd $	$ \surd $
直线	$ \surd $	$ \surd $		$ \surd $	$ \surd $
转弯			$ \surd $
$ h^*_i $	20	20	20	20	20
$ u^*_i $	19.8381	19.8794	19.8517	19.8794	19.9146
$ v^*_i $	0	0	0.0197	0	0.0771
$ w^*_i $	2.5399	2.1933	2.4312	2.1933	1.8449
$ \phi^*_i $	0	$ - $0.0313	0.3495	$ - $0.0313	0
$ \theta^*_i $	0.1273	0.1099	0.1149	0.1099	0.0925
$ \psi^*_i $	0	0	不适用	$ \pi $	$ \pi $
$ p^*_i $	0	0	$ - $0.0229	0	0
$ q^*_i $	0	0	0.0680	0	0
$ r^*_i $	0	0	0.1867	0	0
$ \delta^*_{e,\;i} $	$ - $0.0838	$ - $0.0611	$ - $0.0811	$ - $0.0611	$ - $0.0383
$ \delta^*_{a,\;i} $	0	0.0301	0.0289	0.0301	$ - $0.0127
$ \delta^*_{r,\;i} $	0	0.0132	$ - $0.0110	0.0132	0.0182
$ \delta^*_{t,\;i} $	0.2292	0.2259	0.2276	0.2259	0.2226

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参考文献(31)

[1]	Li Y P, Zhang L X, Cai B, Liang Y. Unified path planning for composite UAVs via Fermat point-based grouping particle swarm optimization. Aerospace Science and Technology, 2024, 148: Article No. 109088 doi: 10.1016/j.ast.2024.109088
[2]	褚跃. 复杂条件下子母式无人机子机系统路径规划研究 [硕士学位论文], 沈阳建筑大学, 中国, 2021. Chu Yue. Research on Path Planning of Sub-machine System of Child-mother UAV Under Complex Conditions [Master thesis], Shenyang Jianzhu University, China, 2021.
[3]	Zhao X D, Wang X Y, Zong G D, Zheng X L. Adaptive neural tracking control for switched high-order stochastic nonlinear systems. IEEE Transactions on Cybernetics, 2017, 47(10): 3088−3099 doi: 10.1109/TCYB.2017.2684218
[4]	Liang Y, Zhu Y M, Yang J N, Zhang L X, Liu M. Tracking control of quadrotor with intermittent target measurements: A stochastic switched systems approach. IEEE Transactions on Aerospace and Electronic Systems, 2023, 59(5): 5302−5313
[5]	Wang Z L, Wang Q, Dong C Y. Asynchronous H_∞ control for unmanned aerial vehicles: Switched polytopic system approach. IEEE/CAA Journal of Automatica Sinica, 2015, 2(2): 207−216 doi: 10.1109/JAS.2015.7081660
[6]	Wang Q, Gong L G, Dong C Y, Zhong K W. Morphing aircraft control based on switched nonlinear systems and adaptive dynamic programming. Aerospace Science and Technology, 2019, 93: Article No. 105325 doi: 10.1016/j.ast.2019.105325
[7]	Chen J, Shi Z K. Flight controller design of transport airdrop. Chinese Journal of Aeronautics, 2011, 24(5): 600−606 doi: 10.1016/S1000-9361(11)60070-8
[8]	Zhang L X, Liang Y, Li Y P, Lu S A, Yang J N. Switched control of fixed-wing aircraft for continuous airdrop of heavy payloads. Journal of Guidance, Control, and Dynamics, 2023, 46(9): 1826−1833 doi: 10.2514/1.G007398
[9]	Han Y J, Liang Y, Zhang L X, Cai B, Li Y P, Li B. Bumpless transfer switched control of aircraft for heavy payload dropping missions. Aerospace Science and Technology, 2024, 148: Article No. 109067 doi: 10.1016/j.ast.2024.109067
[10]	李繁飙, 杨皓月, 王鸿鑫, 阳春华, 廖力清. 基于干扰估计的非对称运动下飞机刹车系统模型预测控制. 自动化学报, 2022, 48(7): 1690−1703 Li Fan-Biao, Yang Hao-Yue, Wang Hong-Xin, Yang Chun-Hua, Liao Li-Qing. Model predictive control of aircraft braking system under asymmetric motion based on disturbance estimation. Acta Automatica Sinica, 2022, 48(7): 1690−1703
[11]	Wu T, Zhu Y M, Zhang L X, Shi P. Bumpless transfer model predictive control for Markov jump linear systems. IEEE Transactions on Automatic Control, 2023, 69(2): 1348−1355
[12]	曹承钰, 李繁飙, 廖宇新, 殷泽阳, 桂卫华. 高超声速变外形飞行器建模与固定时间预设性能控制. 自动化学报, 2024, 50(3): 486−504 Cao Cheng-Yu, Li Fan-Biao, Liao Yu-Xin, Yin Ze-Yang, Gui Wei-Hua. Modeling and fixed-time prescribed performance control for hypersonic morphing vehicle. Acta Automatica Sinica, 2024, 50(3): 486−504
[13]	Drew H, Philipp F, Sun S, Elia K, Davide S. Performance, precision, and payloads: Adaptive nonlinear MPC for quadrotors. IEEE Robotics and Automation Letters, 2021, 7(2): 690−697
[14]	Slegers N, Kyle J, Costello M. Nonlinear model predictive control technique for unmanned-air-vehicles. Journal of Guidance, Control, and Dynamics, 2006, 29(5): 1179−1188 doi: 10.2514/1.21531
[15]	Eren U, Prach A, Koçer B B, Raković S V, Kayacan E, Açkmeşe B. Model predictive control in aerospace systems: Current state and opportunities. Journal of Guidance, Control, and Dynamics, 2017, 40(7): 1541−1566 doi: 10.2514/1.G002507
[16]	Mathur A, Atkins E. Experimental aerodynamic analysis of a quadplane unmanned aircraft system. Journal of Aircraft, 2023, 60(4): 1323−1328 doi: 10.2514/1.C036916
[17]	Hui Z, Kong Y N, Yao W G, Chen G. Aircraft parameter estimation using a stacked long short-term memory network and Levenberg-Marquardt method. Chinese Journal of Aeronautics, 2024, 37(2): 123−136 doi: 10.1016/j.cja.2023.09.002
[18]	Halefom M H, Hopwood J W, Woolsey C A. Unsteady aerodynamics in model-based wind estimation from fixed-wing aircraft motion. Journal of Guidance, Control, and Dynamics, 2024, 47(8): 1556−1568
[19]	Kang Y, Hedrick J K. Linear tracking for a fixed-wing UAV using nonlinear model predictive control. IEEE Transactions on Control Systems Technology, 2009, 17(5): 1202−1210 doi: 10.1109/TCST.2008.2004878
[20]	Mammarella M, Capello E, Dabbene F. Sample-based SMPC for tracking control of fixed-wing UAV. IEEE Control Systems Letters, 2018, 2(4): 611−616 doi: 10.1109/LCSYS.2018.2845546
[21]	Cao R, Liu Y B, Lu Y P. Robust multiple model predictive control for ascent trajectory tracking of aerospace vehicles. IEEE Transactions on Aerospace and Electronic Systems, 2021, 58(2): 1333−1351
[22]	曹煜琪, 付皓然, 高飞, 吕熙敏. 基于MPCC的鸭翼尾座式垂直起降无人机轨迹跟踪控制算法. 航空学报, 2023, 44(S2): 501−511 Cao Yu-Qi, Fu Hao-Ran, Gao Fei, Lv Xi-Min. Trajectory tracking control algorithm for canardequipped tailsitting vertical takeoff and landing UAV based on MPCC. Acta Aeronautica et Astronautica Sinica, 2023, 44(S2): 501−511
[23]	Beard R W, McLain T W. Small Unmanned Aircraft: Theory and Practice. Princeton: Princeton University Press, 2012. 165−173
[24]	Liberzon D. Switching in Systems and Control. Boston: Birkhäuser, 2003. 17−72
[25]	史爽, 费中阳, 赵旭东. 基于时间依赖切换信号的切换系统稳定性分析研究进展. 信息与控制, 2021, 50(1): 34−42 Shi Shuang, Fei Zhong-Yang, Zhao Xu-Dong. Advances on stability analysis for switched systems with time-dependent switching signals. Information and Control, 2021, 50(1): 34−42
[26]	Veer S, Poulakakis I. Switched systems with multiple equilibria under disturbances: Boundedness and practical stability. IEEE Transactions on Automatic Control, 2019, 65(2): 2371−2386
[27]	Nielsen F, Nock R. On the smallest enclosing information disk. Information Processing Letters, 2008, 105(3): 93−97 doi: 10.1016/j.ipl.2007.08.007
[28]	Megiddo N. Linear-time algorithms for linear programming in R³ and related problems. SIAM Journal on Computing, 1983, 12(4): 759−776 doi: 10.1137/0212052
[29]	Phillips K, Campa G, Gururajan S, Seanor B, Napolitano M, Gu Y, et al. Parameter identification for application within a fault-tolerant flight control system. In: Proceedings of the AIAA Atmospheric Flight Mechanics Conference. Chicago, USA: AIAA, 2009. 5723−5743
[30]	Qi P Y, Li Q X, Wang Y N. Trim analysis and structured H-infinity control of wing-docked multibody aircraft. Journal of Guidance, Control, and Dynamics, 2024, 47(5): 964−978 doi: 10.2514/1.G007835
[31]	Erturk S A, Dogan A. Trim analyses of mass-actuated airplane in cruise and steady-state turn. Journal of Aircraft, 2017, 54(4): 1587−1594 doi: 10.2514/1.C034200