动态拓扑下四旋翼无人机集群蜂拥控制

doi:10.12305/j.issn.1001-506X.2024.10.24

Abstract

Abstract:

In view of the cooperative control problem of unmanned aerial vehicle (UAV) swarm without strict configuration constraints under dynamic topology, a flocking control strategy of quadrotor UAV (QUAV) swarm is proposed on the basis of cascade control idea of the inner-outer loop of QUAV. The Kalman-consensus filter (KCF) algorithm is utilized to fuse the communication data with noise, which realizes the accurate estimation of the state of leader with varying velocity. Considering the dynamic variation and scalability requirements of UAV swarm, a flocking control algorithm based on the KCF is designed to realize the position control for the UAV swarm. The stability of the proposed algorithm is proved by the Lyapunov stability theory. An attitude controller is designed for QUAV based on brain emotional learning (BEL) model, which enables the pose control for QUAV. Simulation results prove the validity of control algorithm.

Key words: unmanned aerial vehicle (UAV) swarm, flocking control, dynamic topology, Kalman-consensus filter (KCF), brain emotional learning (BEL)

CLC Number:

V279

Yaxuan YIN, An ZHANG, Wenhao BI, Pan YANG, Zhanjun HUANG. Flocking control for quadrotor unmanned aerial vehicle swarm with dynamic topology[J]. Systems Engineering and Electronics, 2024, 46(10): 3473-3483.

Figures/Tables 8

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References 35

1	LI R, MA H Z. Research on UAV swarm cooperative reconnaissance and combat technology[C]//Proc. of the IEEE 3rd International Conference on Unmanned Systems, 2020: 996-999.
2	齐小刚, 周雨桐, 刘立芳. 无人机集群对地作战任务可靠性评估[J]. 系统工程与电子技术, 2023, 45 (9): 2971- 2978. doi: 10.12305/j.issn.1001-506X.2023.09.38
	Ql X G , ZHOU Y T , LIU L F . Evaluation of the reliability of UAV swarm for ground combat missions[J]. Systems Engineering and Electronics, 2023, 45 (9): 2971- 2978. doi: 10.12305/j.issn.1001-506X.2023.09.38
3	陆晓安, 浦黄忠, 甄子洋, 等. 基于改进一致性算法的无人机集群饱和攻击[J]. 电光与控制, 2021, 28 (8): 31- 35. doi: 10.3969/j.issn.1671-637X.2021.08.007
	LU X A , PU H Z , ZHEN Z Y , et al. Saturation attack of UAV swarm based on improved consensus algorithm[J]. Electronics Optics & Control, 2021, 28 (8): 31- 35. doi: 10.3969/j.issn.1671-637X.2021.08.007
4	冯政, 吴傲, 王谦喆. 无人机集群打击海面目标指定时间协同控制方法[J]. 电光与控制, 2022, 29 (9): 43- 47. doi: 10.3969/j.issn.1671-637X.2022.09.009
	FENG Z , WU A , WANG Q Z . Cooperative control method of designated time for UAV swarm attacking sea target[J]. Electronics Optics & Control, 2022, 29 (9): 43- 47. doi: 10.3969/j.issn.1671-637X.2022.09.009
5	张毅, 于浩, 杨秀霞, 等. 无人机集群分组编队控制跟踪一体化设计[J]. 系统工程与电子技术, 2023, 45 (3): 848- 858. doi: 10.12305/j.issn.1001-506X.2023.03.27
	ZHANG Y , YU H , YANG X X , et al. Integrated design of group formation control and tracking of UAV swarm[J]. Systems Engineering and Electronics, 2023, 45 (3): 848- 858. doi: 10.12305/j.issn.1001-506X.2023.03.27
6	REYNOLDS C W . Flocks, herds, and schools: a distributed behavioral model[J]. Computer Graphics, 1987, 21 (4): 25- 34. doi: 10.1145/37402.37406
7	VICSEK T , CZIROK A , BEN-JACOB E , et al. Novel type of phase transition in a system of self-driven particles[J]. Physical Review Letters, 1995, 75 (6): 1226- 1229. doi: 10.1103/PhysRevLett.75.1226
8	CUCKER F , SMALE S . Emergent behavior in flocks[J]. IEEE Trans. on Automatic Control, 2007, 52 (5): 852- 862. doi: 10.1109/TAC.2007.895842
9	OLFATI-SABER R . Flocking for multi-agent dynamic systems: algorithms and theory[J]. IEEE Trans.on Automatic Control, 2006, 51 (3): 401- 420. doi: 10.1109/TAC.2005.864190
10	GAO J Y , XU X , DING N , et al. Flocking motion of multi-agent system by dynamic pinning control[J]. IET Control Theory & Applications, 2017, 11 (5): 714- 722.
11	YAN T , XU X , LI Z , et al. Flocking of multi-agent system with dynamic topology by pinning control[J]. IET Control Theory & Applications, 2020, 14 (20): 3374- 3381.
12	LIANG Z L , LIU X Z . Hybrid event-triggered impulsive flocking control for multi-agent systems via pinning mechanism[J]. Applied Mathematical Modelling, 2023, 114, 23- 43. doi: 10.1016/j.apm.2022.09.035
13	IZADIPOUR A , GHAISARI J , ASKARI J . Distributed robust adaptive flocking for uncertain nonlinear multi-agent systems with time-varying communication delay[J]. International Journal of Systems Science, 2020, 51 (1): 72- 86. doi: 10.1080/00207721.2019.1694196
14	OLFATI-SABER R , JALALKAMALI P . Coupled distributed estimation and control for mobile sensor networks[J]. IEEE Trans.on Automatic Control, 2012, 57 (10): 2609- 2614. doi: 10.1109/TAC.2012.2190184
15	SU H , CHEN X , CHEN M Z Q , et al. Distributed estimation and control for mobile sensor networks with coupling delays[J]. ISA Transactions, 2016, 64, 141- 150. doi: 10.1016/j.isatra.2016.04.025
16	LUO X Y , LI X L , LI S B , et al. Flocking for multi-agent systems with optimally rigid topology based on information weighted Kalman consensus filter[J]. International Journal of Control, Automation and Systems, 2017, 15 (1): 138- 148. doi: 10.1007/s12555-015-0134-8
17	ZHANG L L , DONG X X , YAO L X , et al. Velocity-varying target tracking of mobile sensor network based on flocking control[J]. Journal of Shanghai Jiaotong University (Science), 2021, 26 (4): 446- 453. doi: 10.1007/s12204-021-2283-7
18	LIU X Y , XIANG X J , CHANG Y , et al. Hierarchical weighting Vicsek model for flocking navigation of drones[J]. Drones, 2021, 5 (3): 74. doi: 10.3390/drones5030074
19	QIU H X , DUAN H B . A multi-objective pigeon-inspired optimization approach to UAV distributed flocking among obstacles[J]. Information Sciences, 2020, 509, 515- 529. doi: 10.1016/j.ins.2018.06.061
20	HUANG F J , WU P L , LI X X . Distributed flocking control of quadrotor UAVs with obstacle avoidance under the parallel-triggered scheme[J]. International Journal of Control, Automation and Systems, 2021, 19 (3): 1375- 1383. doi: 10.1007/s12555-019-0315-y
21	YAN D H , ZHANG W G , CHEN H , et al. Robust control strategy for multi-UAVs system using MPC combined with Kalman-consensus filter and disturbance observer[J]. ISA Transactions, 2023, 135, 35- 51. doi: 10.1016/j.isatra.2022.09.021
22	ARRIETA O , CAMPOS D , RICO-AZAGRA J , et al. Model-based optimization approach for PID control of pitch-roll UAV orientation[J]. Mathematics, 2023, 11 (15): 3390. doi: 10.3390/math11153390
23	LIU N , SHAO X L , LI J , et al. Attitude restricted back-stepping anti-disturbance control for vision based quadrotors with visibility constraint[J]. ISA Transactions, 2020, 100, 109- 125. doi: 10.1016/j.isatra.2019.11.004
24	MARTINEZ-VASQUEZ A H , CASTRO-LINARES R , RODRÍGUEZ-MATA A E , et al. Spherical inverted pendulum on a quadrotor UAV: a flatness and discontinuous extended state observer approach[J]. Machines, 2023, 11 (6): 578. doi: 10.3390/machines11060578
25	HU M Y , LEE K , AHN H , et al. Stabilization and tracking of a quadrotor using modified sigmoid sliding mode control[J]. Sensors, 2022, 22 (10): 3618. doi: 10.3390/s22103618
26	黄国勇. 变推力轴线无人机飞行控制技术研究[D]. 南京: 南京航空航天大学, 2009.
	HUANG G Y. Research on flight control technology of variable thrust axis UAV[D]. Nanjing: Nanjing University of Aeronautics and Astronautics, 2009.
27	WANG H , SHAN J J . Fully distributed event-triggered formation control for multiple quadrotors[J]. IEEE Trans.on Industrial Electronics, 2023, 70 (12): 12566- 12575. doi: 10.1109/TIE.2023.3239870
28	邹立岩, 张明智, 柏俊汝. OODA-L模式下的智能无人集群作战仿真建模框架[J]. 国防科技大学学报, 2021, 43 (4): 163- 170.
	ZOU L Y , ZHANG M Z , BAI J R . Modeling framework for intelligent unmanned swarm operation simulation under OODA-L pattern[J]. Journal of National University of Defense Technology, 2021, 43 (4): 163- 170.
29	YE F , CHEN J , TIAN Y , et al. Cooperative task assignment of a heterogeneous multi-UAV system using an adaptive genetic algorithm[J]. Electronics, 2020, 9 (4): 687. doi: 10.3390/electronics9040687
30	HONG Y G , HU H P , GAO L X . Tracking control for multi-agent consensus with an active leader and variable topology[J]. Automatica, 2006, 42 (7): 1177- 1182. doi: 10.1016/j.automatica.2006.02.013
31	KHALIL H K . Nonlinear systems[M]. New Jersey: Prentice Hall, 2002: 126- 129.
32	AHN S M , CHOI H , HA S Y , et al. On collision-avoiding initial configurations to Cucker-Smale type flocking models[J]. Communications in Mathematical Sciences, 2012, 10 (2): 625- 643. doi: 10.4310/CMS.2012.v10.n2.a10
33	YEGANEH M S O , OSHNOEI A , MIJA-TOVIC N , et al. Intelligent secondary control of islanded AC microgrids: a brain emotional learning-based approach[J]. IEEE Trans.on Industrial Electronics, 2023, 70 (7): 6711- 6723. doi: 10.1109/TIE.2022.3203677
34	HEO J , CHWA D . Robust tracking control using integral sliding mode observer for quadrotors considering motor and propeller dynamics and disturbances[J]. Journal of Electrical Engineering & Technology, 2021, 16 (6): 3247- 3260.
35	VÁŇA P , FAIGL J . Optimal solution of the generalized Dubins interval problem: finding the shortest curvature-constrained path through a set of regions[J]. Autonomous Robots, 2020, 44 (7): 1359- 1376. doi: 10.1007/s10514-020-09932-x

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[4]	Xiaogang QI, Yutong ZHOU, Lifang LIU. Evaluation of the reliability of UAV swarm for ground combat missions [J]. Systems Engineering and Electronics, 2023, 45(9): 2971-2978.
[5]	Shuheng ZHANG, Ruping ZHAI, Yongkai LIU. Identification of UAV swarm type based on fusion features of communication and radar domain [J]. Systems Engineering and Electronics, 2023, 45(12): 3734-3742.
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[9]	Xiaowei FU, Jing PAN. Distributed formation control of UAV swarm with dynamic obstacle avoidance [J]. Systems Engineering and Electronics, 2022, 44(2): 529-537.
[10]	Yang ZHANG, Guangya SI, Yanzheng WANG. Simulation of unmanned aerial vehicle swarm electromagnetic operation concept [J]. Systems Engineering and Electronics, 2020, 42(7): 1510-1518.
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[12]	GAO Yang, LI Dongsheng. Swarm situation perception consensus evaluation via intervalnumber Heronian operators with variable weights [J]. Systems Engineering and Electronics, 2019, 41(1): 89-95.
[13]	SONG Xiaoxue, WEI Lu, LIN Shuisheng. Adaptive synchronization technology of mobile Ad Hoc network [J]. Systems Engineering and Electronics, 2018, 40(9): 2113-2118.

Flocking control for quadrotor unmanned aerial vehicle swarm with dynamic topology

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