Prescribed-time consensus of time-varying open multi-agent systems with delays on time scales

被引:2
作者
Zhou, Boling [1 ,2 ,3 ]
Park, Ju H. [3 ]
Yang, Yongqing [2 ]
Hao, Rixu [2 ]
Jiao, Yu [4 ]
机构
[1] Nanjing Xiaozhuang Univ, Sch Informat Engn, Nanjing, Peoples R China
[2] Jiangnan Univ, Sch Internet Things Engn, Wuxi, Peoples R China
[3] Yeungnam Univ, Dept Elect Engn, Kyonsan, South Korea
[4] Nanjing Inst Technol, Sch Econ & Management, Nanjing, Peoples R China
基金
新加坡国家研究基金会;
关键词
Open multi-agent systems (OMASs); Consensus; Prescribed-time; Impulsive; Observer; Time scales; STATE ESTIMATION; NETWORKS;
D O I
10.1016/j.ins.2024.120957
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In this study, we focus on prescribed-time leader-following consensus problems for a class of time-varying open multi-agent systems (OMASs) with time delays on time scales. To achieve this objective, we propose a novel segmented state feedback control protocol which contains a time-varying scalar function. It ensures prescribed-time consensus can be achieved while the monotonicity of Lyapunov function is unknown. On this basis, impulsive signals dependent on the leader are further introduced at each opening instant to avoid the possibility of the controller norm being too large. During the process of theoretical analysis, we further innovatively extend Halanay-like inequalities on time scales to resolve theoretical analysis difficulties caused by time delays. Based on time scale theory and Lyapunov stability theory, sufficient conditions depending on system parameters and controller parameters for achieving prescribed-time consensus can be derived. Besides, considering absolute information of each agent cannot be completely obtained, we further design one observer system to reconstruct information of the original system, guaranteeing it can still reach consensus within the pre-set time. Finally, two simulation examples are used to illustrate the validity of our proposed theory.
引用
收藏
页数:19
相关论文
共 50 条
[31]   A distributed prescribed-time optimization analysis for multi-agent systems [J].
Chen, Siyu ;
Jiang, Haijun ;
Yu, Zhiyong .
INFORMATION SCIENCES, 2022, 607 :346-360
[32]   Consensus Analysis of Heterogeneous Multi-Agent Systems with Time-Varying Delay [J].
Wang, Beibei ;
Sun, Yuangong .
ENTROPY, 2015, 17 (06) :3631-3644
[33]   Regional consensus in discrete-time multi-agent systems subject to time-varying delays and saturating actuators [J].
Silva, Thales C. ;
Leite, Valter J. S. ;
Souza, Fernando O. ;
Pimenta, Luciano C. A. .
INTERNATIONAL JOURNAL OF CONTROL, 2023, 96 (06) :1457-1469
[34]   Consensus in multi-agent systems over time-varying networks [J].
Mahmoud M.S. ;
Oyedeji M. .
Cyber-Physical Systems, 2020, 6 (03) :117-145
[35]   Distributed fixed-time and prescribed-time average consensus for multi-agent systems with energy constraints [J].
Yan, Ke-Xing ;
Han, Tao ;
Xiao, Bo ;
Yan, Huaicheng .
INFORMATION SCIENCES, 2023, 647
[36]   Consensus of multi-agent systems with impulsive perturbations and time-varying delays by dynamic delay interval method [J].
Shan, Qihe ;
Chen, Zengzhi ;
Li, Tieshan ;
Chen, C. L. Philip .
COMMUNICATIONS IN NONLINEAR SCIENCE AND NUMERICAL SIMULATION, 2019, 78
[37]   Multi-agent consensus with heterogeneous time-varying input and communication delays in digraphs [J].
Jiang, Wei ;
Liu, Kun ;
Charalambous, Themistoklis .
AUTOMATICA, 2022, 135
[38]   Consensus of Second-Order Multi-Agent Systems with Time-Varying Delays and Antagonistic Interactions [J].
Bo Hou ;
Fuchun Sun ;
Hongbo Li ;
Guangbin Liu .
TsinghuaScienceandTechnology, 2015, 20 (02) :205-211
[39]   Bipartite Consensus for Multi-Agent Systems With Time-Varying Delays Based on Method of Delay Partitioning [J].
Zhang, Xiaodan ;
Liu, Kaien ;
Ji, Zhijian .
IEEE ACCESS, 2019, 7 :29285-29294
[40]   Consensus for multi-agent systems under double integrator dynamics with time-varying communication delays [J].
Liu, Kaien ;
Xie, Guangming ;
Wang, Long .
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL, 2012, 22 (17) :1881-1898