Please wait a minute...
文章检索
复杂系统与复杂性科学  2022, Vol. 19 Issue (3): 81-87    DOI: 10.13306/j.1672-3813.2022.03.010
  本期目录 | 过刊浏览 | 高级检索 |
脉冲控制下半马尔可夫随机MAS的均方一致性
冯万典, 彭世国, 曾梓贤
广东工业大学自动化学院, 广州 510006
Mean-square Consensus of Semi-markov Stochastic MAS via Impulsive Control
FENG Wandian, PENG Shiguo, ZENG Zixian
School of Automation, Guangdong University of Technology, Guangzhou 510006, China
全文: PDF(1481 KB)  
输出: BibTeX | EndNote (RIS)      
摘要 针对多智能体系统会受到外部干扰而使系统结构随机发生改变的问题,提出了当切换信号服从半马尔可夫过程时,领导跟随随机多智能体系统实现均方一致的控制算法。运用代数图论、半马尔可夫过程的转移速率与驻留时间分布函数相关性质和Lyapunov稳定性理论等理论工具,对控制算法进行了稳定性分析。通过设计合适的脉冲控制协议,给出了系统实现均方一致性的充分条件。条件表明,若脉冲间隔具有某一上界,均方一致性仍可实现。最后,数值仿真验证了结果的有效性。
服务
把本文推荐给朋友
加入引用管理器
E-mail Alert
RSS
作者相关文章
冯万典
彭世国
曾梓贤
关键词 多智能体系统半马尔可夫过程脉冲控制均方一致性    
Abstract:Aiming at the problem that the multi-agent system structure will change randomly due to external disturbances, a mean-square consensus control algorithm is proposed for leader-follower multi-agent system when switching signals obey semi-Markov process. The stability of the control algorithm is analyzed by algebraic graph theory, the properties of the transition rate and the distribution function of the dwell time of semi-Markov procession and Lyapunov stability theory. The results show that sufficient conditions for the system to achieve mean square consensus is given by the designed impulsive control protocol. In addition, if the pulse interval has an upper bound, the mean square consensus can still be achieved. Finally, the validity of the proposed condition is verified by the numerical example.
Key wordsmulti-agent systems    semi-Markov process    impulsive control    mean-square consensus
收稿日期: 2021-06-21      出版日期: 2022-10-12
ZTFLH:  TP13  
基金资助:国家自然科学基金(61973092); 广东省基础与应用基础研究基金(2019A1515012104)
作者简介: 冯万典(1995-),男,广东湛江人,硕士研究生,主要研究方向为多智能体系统一致性和半马尔可夫跳变系统。
引用本文:   
冯万典, 彭世国, 曾梓贤. 脉冲控制下半马尔可夫随机MAS的均方一致性[J]. 复杂系统与复杂性科学, 2022, 19(3): 81-87.
FENG Wandian, PENG Shiguo, ZENG Zixian. Mean-square Consensus of Semi-markov Stochastic MAS via Impulsive Control. Complex Systems and Complexity Science, 2022, 19(3): 81-87.
链接本文:  
https://fzkx.qdu.edu.cn/CN/10.13306/j.1672-3813.2022.03.010      或      https://fzkx.qdu.edu.cn/CN/Y2022/V19/I3/81
[1] GUO G, WEN S. Communication scheduling and control of a platoon of vehicles in VANETs[J]. IEEE Transactions on Intelligent Transportation Systems, 2015, 17(6): 1551-1563.
[2] VILARINHO C, TAVARES J P, ROSSETTI R J F. Design of a multiagent system for real-time traffic control[J]. IEEE Intelligent Systems, 2016, 31(4): 68-80.
[3] WEN S, GUO G. Sampled-data control for connected vehicles with Markovian switching topologies and communication delay[J]. IEEE Transactions on Intelligent Transportation Systems, 2019, 21(7): 2930-2942.
[4] DING D, WANG Z, DANIEL W C H, et al. Observer-based event-triggering consensus control for multiagent systems with lossy sensors and cyber-attacks[J]. IEEE Transactions on cybernetics, 2016, 47(8): 1936-1947.
[5] YE D, ZHANG T Y, GUO G. Stochastic coding detection scheme in cyber-physical systems against replay attack[J]. Information Sciences, 2019, 481: 432-444.
[6] LI W, JIA Y. Consensus-based distributed multiple model UKF for jump Markov nonlinear systems[J]. IEEE Transactions on Automatic Control, 2011, 57(1): 227-233.
[7] YOU K, LI Z, XIE L. Consensus condition for linear multi-agent systems over randomly switching topologies[J]. Automatica, 2013, 49(10): 3125-3132.
[8] GE X, HAN Q L. Consensus of multiagent systems subject to partially accessible and overlapping Markovian network topologies[J]. IEEE Transactions on Cybernetics, 2016, 47(8): 1807-1819.
[9] SAKTHIVEL R, SAKTHIVEL R, KAVIARASAN B, et al. Leader-following exponential consensus of input saturated stochastic multi-agent systems with Markov jump parameters[J]. Neurocomputing, 2018, 287: 84-92.
[10] DONG S, REN W, W U Z G. Observer-based distributed mean-square consensus design for leader-following multiagent markov jump systems[J]. IEEE Transactions on Cybernetics, 2021,51(6):3054-3061.
[11] HUANG J. Analysis and synthesis of semi-Markov jump linear systems and networked dynamic systems[D]. Victoria : University of Victoria, 2013.
[12] SHI P, LI F, WU L, et al. Neural network-based passive filtering for delayed neutral-type semi-Markovian jump systems[J]. IEEE Transactions on Neural Networks and Learning Systems, 2016, 28(9): 2101-2114.
[13] HUANG J, SHI Y. Stochastic stability and robust stabilization of semi‐Markov jump linear systems[J]. International Journal of Robust and Nonlinear Control, 2013, 23(18): 2028-2043.
[14] WANG H, XUE B, XUE A. Leader-following consensus control for semi-Markov jump multi-agent systems: an adaptive event-triggered scheme[J]. Journal of the Franklin Institute, 2021, 358(1): 428-447.
[15] DAI J, GUO G. Exponential consensus of non-linear multi-agent systems with semi-Markov switching topologies[J]. IET Control Theory & Applications, 2017, 11(18): 3363-3371.
[16] DAI J, GUO G. Event-triggered leader-following consensus for multi-agent systems with semi-Markov switching topologies[J]. Information Sciences, 2018, 459: 290-301.
[17] LI X, CAO J, DANIEL WC H. Impulsive control of nonlinear systems with time-varying delay and applications[J]. IEEE Transactions on Cybernetics, 2020, 50(6): 2661-2673.
[18] HUA M, ZHANG L, YAO F, et al. Robust H filtering for continuous-time nonhomogeneous Markov jump nonlinear systems with randomly occurring uncertainties[J]. Signal Processing, 2018, 148: 250-259.
[19] WU Z G, SHI P, SU H, et al. Asynchronous L2-L filtering for discrete-time stochastic Markov jump systems with randomly occurred sensor nonlinearities[J]. Automatica, 2014, 50(1): 180-186.
[20] WEI Y, QIU J, KARIMI H R, et al. A novel memory filtering design for semi-Markovian jump time-delay systems[J]. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2017, 48(12): 2229-2241.
[21] LU J, DANIEL W C H, CAO J. A unified synchronization criterion for impulsive dynamical networks[J]. Automatica, 2010, 46(7): 1215-1221.
[1] 张志伟, 纪志坚. 有向路径下的一类多智能体系统的能控性分析[J]. 复杂系统与复杂性科学, 2022, 19(2): 63-70.
[2] 国俊豪, 纪志坚. 基于NE结果的多智能体系统模型及其能控性[J]. 复杂系统与复杂性科学, 2021, 18(4): 50-57.
[3] 王潇, 纪志坚. 基于MAS的合作—竞争编队研究[J]. 复杂系统与复杂性科学, 2021, 18(1): 8-14.
[4] 李英桢, 纪志坚, 刘帅, 杨仪龙. 含时滞多智能体系统的边动态二分一致性[J]. 复杂系统与复杂性科学, 2019, 16(4): 19-30.
[5] 王潇, 纪志坚. 基于MAS的无人机新型编队算法[J]. 复杂系统与复杂性科学, 2019, 16(2): 60-68.
[6] 仉伟, 纪志坚, 渠继军. 基于领导者对称的多智能体系统可控性研究[J]. 复杂系统与复杂性科学, 2019, 16(2): 52-59.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed