具有弱通讯的多智能体分布式自适应协同跟踪控制

doi:10.12305/j.issn.1001-506X.2021.02.23

Abstract

Abstract:

A novel distributed adaptive backstepping control method is proposed for high-order strict feedback nonlinear multi-agent systems with weak communication. And the cooperative tracking control problem of the system is studied. Firstly, five agents are taken as the controlled objects, one of them is formed the "leader follower" formation mode in a distributed structure. The leader's velocity is taken as the forward speed of the whole formation system, and the other agents follow the leader's formation movement as followers. Secondly, the adaptive inversion method is used to estimate the uncertain parameters of the system due to weak communication, and a compensation tracking control law is designed for the system, so that the agents in the system can realize autonomous tracking of time-varying reference trajectory, and avoid obstacles with the optimal trajectory ultimately maintain the desired formation motion. Then, according to Lyapunov stability theory, the effectiveness of the proposed control law is proved. Finally, the simulation results show that the proposed control law can make the lateral and longitudinal tracking errors and the relative errors of the reference trajectory converge rapidly, and keep the system asymptotically stable in the tracking process.

Key words: weak communication, multi-agent system, back-stepping technology, consensus tracking, rapid convergence

CLC Number:

TP237

Pu ZHANG, Huifeng XUE, Shan GAO, Xuan ZUO. Distributed adaptive cooperative tracking control of multi-agent system with weak communication[J]. Systems Engineering and Electronics, 2021, 43(2): 487-498.

Figures/Tables 15

Fig.1

Fig.2

Fig.3

Table 1

Fig.4

Fig.5

Fig.6

Fig.7

Fig.8

Fig.9

Fig.10

Fig.11

Fig.12

Fig.13

Table 2

References 32

1	张志伟, 滕英元, 杨慧欣, 等. 具有速度、加速度约束的机器人编队避障控制[J]. 控制理论与应用, 2020, 37 (6): 1388- 1396.
	ZHANG Z W , TENG Y Y , YANG H X , et al. Obstacle avoidance control for robots formation with speed and acceleration constraints[J]. Control Theory & Applications, 2020, 37 (6): 1388- 1396.
2	张志伟, 滕英元. 机器人编队协同控制方法综述[J]. 机电信息, 2019, (32): 28- 30. doi: 10.3969/j.issn.1671-0797.2019.32.015
	ZHANG Z W , TENG Y Y . Overview of collaborative control methods for robot formation[J]. Mechanical and Electrical Information, 2019, (32): 28- 30. doi: 10.3969/j.issn.1671-0797.2019.32.015
3	芮可人, 王丽华, 谢能刚. 基于虚拟结构优化模型的多机器人编队形成方法[J]. 现代信息科技, 2019, 3 (18): 56- 58.
	RUI K R , WANG L H , XIE N G . Formation method of multi-robot formation based on virtual structure optimization model[J]. Modern Information Technology, 2019, 3 (18): 56- 58.
4	ZHANG J L , YAN J G , ZHANG P . Multi-UAV formation control based on a novel back-stepping approach[J]. IEEE Trans.on Vehicular Technology, 2020, 69 (3): 2437- 2448. doi: 10.1109/TVT.2020.2964847
5	WEN G G , ZHAI X Q , PENG Z X , et al. Fault-tolerant secure consensus tracking of delayed nonlinear multi-agent systems with deception attacks and uncertain parameters via impulsive control[J]. Communications in Nonlinear Science and Numerical Simulation, 2020, 82, 105043. doi: 10.1016/j.cnsns.2019.105043
6	CHENG Y , UGRINOVSII V . Event-triggered leader-following tracking control for multivariable multi-agent systems[J]. Automatica, 2016, 70, 204- 210. doi: 10.1016/j.automatica.2016.04.003
7	HU J P , FENG G . Distributed tracking control of leader-follower multi-agent systems under noisy measurement[J]. Automatica, 2010, 46 (8): 1382- 1387. doi: 10.1016/j.automatica.2010.05.020
8	BEN-OR M , GOLDWASSER S , WIGDERSON A . Completeness theorems for non-cryptographic fault-tolerant distributed computation[M]. Jerusalem: Hebrew University Press, 2019.
9	ZHAO B , LIU D R , LI Y C . Observer based adaptive dynamic programming for fault tolerant control of a class of nonlinear systems[J]. Information Sciences, 2017, (384): 21- 33.
10	WANG J , LIANG K , HUANG X , et al. Dissipative fault-tolerant control for nonlinear singular perturbed systems with Markov jumping parameters based on slow state feedback[J]. Applied Mathematics & Computation, 2018, 328, 247- 262.
11	SHI G D , HONG Y G . Global target aggregation and state agreement of nonlinear multi-agent systems with switching topologies[J]. Automatica, 2009, 45 (5): 1165- 1175. doi: 10.1016/j.automatica.2008.12.015
12	YU W , ZHENG W X , CHEN G , et al. Second-order consensus in multi-agent dynamical systems with sampled position data[J]. Automatica, 2011, 47 (7): 1496- 1503. doi: 10.1016/j.automatica.2011.02.027
13	OLIVEIRA L B , CAMPONOGARA E . Multi-agent model predictive control of signaling split in urban traffic networks[J]. Transportation Research Part C: Emerging Technologies, 2010, 18 (1): 120- 139. doi: 10.1016/j.trc.2009.04.022
14	GUERRA E , BOLEA Y , GAMIZ J , et al. Design and implementation of a virtual sensor network for smart waste water monitoring[J]. Sensors, 2020, 20 (2): 358. doi: 10.3390/s20020358
15	HAN Y , ZHANG K , LI H , et al. MAS-based distributed coordinated control and optimization in microgrid and microgrid clusters: a comprehensive overview[J]. IEEE Trans.on Power Electronics, 2017, 33 (8): 6488- 6508.
16	LIU R T , BURKE T A , ABRAMSON L Y , et al. The behavioral approach system (BAS) model of vulnerability to bipolar disorder: evidence of a continuum in BAS sensitivity across adolescence[J]. Journal of Abnormal Child Psychology, 2018, 46 (6): 1333- 1349. doi: 10.1007/s10802-017-0363-9
17	CHEN S M , PEI H Q , LAI Q , et al. Multitarget tracking control for coupled heterogeneous inertial agents systems based on flocking behavior[J]. IEEE Trans.on Systems, Man, and Cybernetics: Systems, 2019, 49 (12): 2605- 2611. doi: 10.1109/TSMC.2017.2789335
18	LI J, XUE D R, ZHANG J X. Multi-UUV formation coordination control based on combination of virtual structure and leader[C]//Proc.of the IEEE International Conference on Mechatronics and Automation, 2018: 1574-1579.
19	刘安东,秦冬冬,金哲豪,等.一种基于虚拟结构法的多移动机器人分布式预测控制方法[P].中国: CN201910693124.5, 2020-01-17.
	LIU A D, QIN D D, JIN Z H, et al. A distributed predictive control for multiple mobile robots based on virtual structure method[P]. China: CN201910693124.5, 2020-01-17.
20	HE W , ZHANG B , HAN Q L , et al. Leader-following consensus of nonlinear multi-agent systems with stochastic sampling[J]. IEEE Trans.on Cybernetics, 2016, 47 (2): 327- 338.
21	YAN C , FANG H Z , CHAO H Y . Energy-aware leader-follower tracking control for electric-powered multi-agent systems[J]. Control Engineering Practice, 2018, 79, 209- 218. doi: 10.1016/j.conengprac.2018.07.013
22	NING B , HAN Q L , LU Q . Fixed-time leader-following consensus for multiple wheeled mobile robots[J]. IEEE Trans.on Cybernetics, 2019, 50 (10): 4381- 4392.
23	BAINY R G , SILVA K , LOTFIFARD S , et al. Dynamic zone selection for busbar protection based on graph theory and boolean algebra[J]. IEEE Trans.on Power Delivery, 2020, 35 (4): 1769- 1778. doi: 10.1109/TPWRD.2019.2953594
24	YING K Z. Flight path planning of agriculture UAV based on improved artificial potential field method[C]//Proc.of the IEEE Chinese Control and Decision Conference, 2018: 1526-1530.
25	REN W, MOORE K, CHEN Y Q. High-order consensus algorithms in cooperative vehicle systems[C]//Proc.of the IEEE International Conference on Networking, Sensing and Control, 2006: 457-462.
26	LIU J , FANG J A , LI Z , et al. Time-varying formation tracking for second-order multi-agent systems subjected to switching topology and input saturation[J]. International Journal of Control, Automation and Systems, 2020, 18 (4): 991- 1001. doi: 10.1007/s12555-019-0473-y
27	YU W , ZHENG W X , CHEN G , et al. Second-order consensus in multi-agent dynamical systems with sampled position data[J]. Automatica, 2011, 47 (7): 1496- 1503. doi: 10.1016/j.automatica.2011.02.027
28	WANG W , HUANG C , HUANG C X , et al. Bipartite formation problem of second-order nonlinear multi-agent systems with hybrid impulses[J]. Applied Mathematics and Computation, 2020, 370, 124926. doi: 10.1016/j.amc.2019.124926
29	ISLAM S , XIROS N I . Robust asymptotic and finite-time tracking for second-order nonlinear multi-agent autonomous systems[J]. International Journal of Control, Automation and Systems, 2019, 17 (12): 3069- 3078. doi: 10.1007/s12555-018-0470-6
30	REN W , BEARD R W . Consensus seeking in multiagent systems under dynamically changing interaction topologies[J]. IEEE Trans.on Automatic Control, 2005, 50 (5): 655- 661. doi: 10.1109/TAC.2005.846556
31	HU J L , SUN X X , HE L . Formation tracking for nonlinear multi-agent systems with input and output quantization via adaptive output feedback control[J]. Journal of Systems Science and Complexity, 2020, 33, 401- 425. doi: 10.1007/s11424-019-8087-2
32	LI J S , LI J M . Distributed adaptive fuzzy iterative learning control of coordination problems for higher order multi-agent systems[J]. International Journal of Systems Science, 2016, 47 (10): 2318- 2329. doi: 10.1080/00207721.2014.993139

智能体编号	(x₀, y₀)/m	(δ_ix, δ_iy)/m	(${\hat \theta } $_ix, ${\hat \theta } $_iy)
智能体#1	(1, 2)	(1, 3)	(3, 6)
智能体#2	(2, 1)	(1, 1)	(5, 2)
智能体#3	(3, 3)	(4, 3)	(4, 3)
智能体#4	(2, 5)	(4, 1)	(7, 1)
智能体#5	(4, 2)	(6, 2)	(10, 4)

方法	稳态误差/m	稳定时间/s
所提方法	0.62	7.1
SMC方法	2.32	16.3
ACM方法	1.61	13.1

[1]	Zonggang LI, Jintao QIU, Xiaogang NING, Yinjuan CHEN. Dynamic periodic event-triggered bipartite consensus for multi-agent systems [J]. Systems Engineering and Electronics, 2026, 48(1): 278-289.
[2]	Fangjie GUO, Jing LI, Zhaohui ZHANG. Predefined-time lag consensus for MAS with input delay [J]. Systems Engineering and Electronics, 2025, 47(9): 3041-3046.
[3]	Jun JIANG, Jiarui ZHANG, Jilong PAN, Guolin SUN. Edge model collaboration and data compression algorithm for unmanned systems in sea [J]. Systems Engineering and Electronics, 2025, 47(5): 1718-1727.
[4]	Ziyi WANG, Xiongjun FU, Jian DONG, Cheng FENG. Optimization of radar collaborative anti-jamming strategies based on hierarchical multi-agent reinforcement learning [J]. Systems Engineering and Electronics, 2025, 47(4): 1108-1114.
[5]	Jiale LI, Qilin ZHONG, Jie XIAO, Guofei LI. Adaptive fixed-time formation control for multi-agent system [J]. Systems Engineering and Electronics, 2025, 47(2): 600-607.
[6]	Chen WANG, Cheng ZHU, Xiangke WANG, Zhaoyun DING, Qianzhen ZHANG, Sheng ZHANG, Xianqiang ZHU. Technology for countering dynamic multi-target motion control using distributed drone swarm systems [J]. Systems Engineering and Electronics, 2025, 47(11): 3765-3778.
[7]	Weimin IU, Yongyue WANG, Xinyang MA, Jinkun LIU. Consensus control for input-delay multi-agent system with input constraint [J]. Systems Engineering and Electronics, 2024, 46(9): 3176-3184.
[8]	Jie ZHANG, Kairong LIU, Jinbao CHEN, Yingxue ZHANG, Chuanzhi CHEN, Hongzhi YU, Yunxiao ZHANG. Multi-agents formation control method based on space confrontation [J]. Systems Engineering and Electronics, 2024, 46(6): 2082-2091.
[9]	Guhao SUN, Zhongze CAI, Qingshuang ZENG. Fixed-time distributed tracking and control of multi-agent formation weighted centroid [J]. Systems Engineering and Electronics, 2024, 46(12): 4165-4172.
[10]	Pu ZHANG, Huifeng XUE, Shan GAO, Xuan ZUO. Distributed finite-time adaptive cooperative fault-tolerant control for multi-agent systems with integrated actuators faults [J]. Systems Engineering and Electronics, 2022, 44(4): 1220-1229.
[11]	Zhe LUO, Wanzhen QUAN, Purui ZHANG, Xiaogang YANG. Consensus tracking control for one-side Lipschitz nonlinear multi-agent systems [J]. Systems Engineering and Electronics, 2022, 44(1): 279-284.
[12]	Jiayi LIU, Shaohua YUE, Gang WANG, Xiaoqiang YAO, Jie ZHANG. Cooperative evolution algorithm of multi-agent system under complex tasks [J]. Systems Engineering and Electronics, 2021, 43(4): 991-1002.
[13]	Ang GAO, Zhiming DONG, Liang LI, Jinghua SONG, Li DUAN. Parallel priority experience replay mechanism of MADDPG algorithm [J]. Systems Engineering and Electronics, 2021, 43(2): 420-433.
[14]	Jiayi LIU, Gang WANG, Jie ZHANG, Chuang WANG, Xituan SONG. Target optimal assignment model based on improved AGD-distributed multi-Agent system [J]. Systems Engineering and Electronics, 2020, 42(4): 863-870.
[15]	ZHOU Jian, GONG Chunlin, GU Liangxian, SU Hua. Distributed synchronization of leader-follower systems with unmatched uncertainties [J]. Systems Engineering and Electronics, 2019, 41(3): 636-642.

Distributed adaptive cooperative tracking control of multi-agent system with weak communication

RichHTML

PDF (PC)

Knowledge

Abstract

Cite this article

share this article

Figures/Tables 15

References 32

Related Articles 15

Recommended Articles

Metrics

Comments