分布式边界控制下多智能体系统的输出一致性
Output Consensus of Multi-Agent Systems under Distributed Boundary Control
摘要: 探讨了多智能体系统和无向拓扑中的分布式测量边界控制问题，根据智能体及其邻域之间的通信所产生的信息，在空间边界点上进行边界控制器的设计。本文利用李雅普诺夫第二方法建立了输出一致性充分条件，并通过线性矩阵不等式计算得出控制增益。最后，通过数值算例来证明理论分析的结果。
Abstract: The problem of distributed measurement boundary control in multi-agent systems and undirected topologies is explored, and the design of boundary controllers is carried out at spatial boundary points based on the information generated by the communication between the agents and their neighbors. In this paper, a sufficient condition for output consensus is established using Liapunov’s second method, and the control gain is computed by linear matrix inequality. Finally, the results of the theoretical analysis are demonstrated by numerical examples.
文章引用：杨梓鹏, 张荣强, 刘琛. 分布式边界控制下多智能体系统的输出一致性[J]. 动力系统与控制, 2024, 13(4): 145-152. https://doi.org/10.12677/dsc.2024.134014

参考文献

[1] 路则欢, 张志强, 孙元功. 有限域上多智能体系统的分布式协同控制研究综述[J/OL]. 控制与决策: 1-8. 2024-06-18.[CrossRef] 
[2] 王君, 杨嘉琦. 异构多智能体系统固定时间容错输出一致性研究[J/OL]. 系统科学与数学: 1-21.
http://kns.cnki.net/kcms/detail/11.2019.O1.20240209.1212.002.html, 2024-06-18.
[3] 牟瑞. 多智能体系统分布式事件触发一致性控制[D]: [博士学位论文]. 济南: 山东大学, 2023.
[4] Degroot, M.H. (1974) Reaching a Consensus. Journal of the American Statistical Association, 69, 118-121. [Google Scholar] [CrossRef] 
[5] Reynolds, C.W. (1987) Flocks, Herds and Schools: A Distributed Behavioral Model. Proceedings of the 14th Annual Conference on Computer Graphics and Interactive Techniques, Anaheim, 27-31 July 1987, 25-34. [Google Scholar] [CrossRef] 
[6] Vicsek, T., Czirók, A., Ben-Jacob, E., Cohen, I. and Shochet, O. (1995) Novel Type of Phase Transition in a System of Self-Driven Particles. Physical Review Letters, 75, 1226-1229. [Google Scholar] [CrossRef] [PubMed]
[7] Jadbabaie, A., Jie Lin, and Morse, A.S. (2003) Coordination of Groups of Mobile Autonomous Agents Using Nearest Neighbor Rules. IEEE Transactions on Automatic Control, 48, 988-1001. [Google Scholar] [CrossRef] 
[8] Olfati-Saber, R. and Murray, R.M. (2004) Consensus Problems in Networks of Agents with Switching Topology and Time-delays. IEEE Transactions on Automatic Control, 49, 1520-1533. [Google Scholar] [CrossRef] 
[9] Qiu, Q. and Su, H. (2022) Distributed Adaptive Consensus of Parabolic PDE Agents on Switching Graphs with Relative Output Information. IEEE Transactions on Industrial Informatics, 18, 297-304. [Google Scholar] [CrossRef] 
[10] Yan, X., Yang, C., Cao, J., Korovin, I., Gorbachev, S. and Gorbacheva, N. (2022) Boundary Consensus Control Strategies for Fractional-Order Multi-Agent Systems with Reaction-Diffusion Terms. Information Sciences, 616, 461-473. [Google Scholar] [CrossRef] 
[11] Ferrari-Trecate, G., Buffa, A. and Gati, M. (2006) Analysis of Coordination in Multi-Agent Systems through Partial Difference Equations. IEEE Transactions on Automatic Control, 51, 1058-1063. [Google Scholar] [CrossRef] 
[12] Wang, Y., Song, Y., Hill, D.J. and Krstic, M. (2019) Prescribed-time Consensus and Containment Control of Networked Multiagent Systems. IEEE Transactions on Cybernetics, 49, 1138-1147. [Google Scholar] [CrossRef] [PubMed]
[13] Lin, B., Luo, S. and Jiang, Y. (2023) Mean-square Output Consensus of Heterogeneous Multi-Agent Systems with Multiplicative Noises in Dynamics and Measurements. Journal of Systems Science and Complexity, 36, 2364-2381. [Google Scholar] [CrossRef] 
[14] Wang, X. and Huang, N. (2021) Finite-time Consensus of Multi-Agent Systems Driven by Hyperbolic Partial Differential Equations via Boundary Control. Applied Mathematics and Mechanics, 42, 1799-1816. [Google Scholar] [CrossRef] 
[15] Zhou, Q. and Li, B. (2023) Numerical Analysis of a Neumann Boundary Control Problem with a Stochastic Parabolic Equation. Science China Mathematics, 66, 2133-2156. [Google Scholar] [CrossRef] 
[16] Wu, H., Wang, J. and Li, H. (2014) Fuzzy Boundary Control Design for a Class of Nonlinear Parabolic Distributed Parameter Systems. IEEE Transactions on Fuzzy Systems, 22, 642-652. [Google Scholar] [CrossRef] 
[17] 王怡. 基于PI控制的一阶积分-微分型双曲偏微分方程的边界镇定性[D]: [硕士学位论文]. 济南: 山东大学, 2023.
[18] 高普阳, 赵子桐, 杨扬. 基于卷积神经网络模型数值求解双曲型偏微分方程的研究[J]. 应用数学和力学, 2021, 42(9): 932-947.

为你推荐