删除或更新信息,请邮件至freekaoyan#163.com(#换成@)

带有初态误差的高阶多智能体系统一致性跟踪

本站小编 Free考研考试/2021-12-27

带有初态误差的高阶多智能体系统一致性跟踪 李国军1,2, 陈东杰2, 韩一士21. 浙江工业大学信息工程学院, 杭州 310023;
2. 浙江警察学院公共基础部, 杭州 310053 Consensus Tracking of High-order Multi-agent Systems with Initial State Errors LI Guojun1,2, CHEN Dongjie2, HAN Yishi21. College of Information Engineering, Zhejiang University of Technology, Hangzhou 310023, China;
2. Basic Courses Department, Zhejiang Police College, Hangzhou 310053, China
摘要
图/表
参考文献
相关文章(15)
点击分布统计
下载分布统计
-->

全文: PDF(714 KB) HTML (1 KB)
输出: BibTeX | EndNote (RIS)
摘要本文借助迭代学习控制方法,针对一类在有限区间上执行重复任务的高阶多智能体,提出一种一致性跟踪算法.在跟踪过程中,通过对状态误差的修正,实现了一致性跟踪.在修正过程中,系统在某段时间内只修正某一种初态误差,当这种初态误差的修正操作完成以后紧接着开始下一种初态误差的修正,以此类推,最终实现所有初态误差的完全修正,并且所有修正操作在一个指定的时间内完成.最后,通过仿真算例验证了所提算法的有效性.
服务
加入引用管理器
E-mail Alert
RSS
收稿日期: 2017-05-10
PACS:O212.7

引用本文:
李国军, 陈东杰, 韩一士. 带有初态误差的高阶多智能体系统一致性跟踪[J]. 应用数学学报, 2018, 41(2): 156-171. LI Guojun, CHEN Dongjie, HAN Yishi. Consensus Tracking of High-order Multi-agent Systems with Initial State Errors. Acta Mathematicae Applicatae Sinica, 2018, 41(2): 156-171.
链接本文:
http://123.57.41.99/jweb_yysxxb/CN/ http://123.57.41.99/jweb_yysxxb/CN/Y2018/V41/I2/156


[1] Vicsek T, Czirók A, Ben-Jacob E, Cohen I, Shochet O. Novel type of phase transition in a system of self-driven particles. Physical Review Letters, 1995, 75(6):1226-1229
[2] Jadbabaie A, Lin J, Morse A. Coordination of groups of mobile autonomous agents using nearest neighbor rules. IEEE Trans. Autom. Control, 2003, 48(6):988-1001
[3] 关永强, 纪志坚, 张霖, 王龙. 多智能体系统能控性研究进展. 控制理论与应用, 2015, 32(4):421-431(Guan Y, Ji Z, Zhang L, Wang L. Recent developments on controllability of multi-agent systems. Control Theory & Applications, 2017, 34(3):401-407)
[4] Ren W, Beard R, Atkins E. Information consensus in multivehicle cooperative control. IEEE Control Systems Magazine, 2007, 27(2):71-82
[5] Meng D, Jia Y. Formation control for multi-agent systems through an iterative learning design approach. International Journal of Robust & Nonlinear Control, 2014, (24):340-361
[6] Fax J, Murray R. Information flow and cooperative control of vehicle formations. IEEE Trans. Autom. Control, 2004, 49(9):1465-1476
[7] Olfati-Saber R, Murray M. Consensus problems in networks of agents with switching topology and time-delays. IEEE Trans. Autom. Control, 2004, 49(9):1520-1533
[8] Zhu W, Cheng D. Leader-following consensus of second-order agents with multiple time-varying delays. Automatica, 2010, 46(12):1994-1999
[9] Ren W. Second-order consensus algorithm with extensions to switching topologies and reference models. In:Proceedings of the IEEE American Control Conference. New York:IEEE, 2007, 1431-1436
[10] Khan U. High Dimensional Consensus in Large-scale Networks:Theory and Applications. Carnegie Mellon University, USA, 2009
[11] Huang Q. Consensus analysis of multi-agent discrete-time systems. Acta Automatica Sinica, 2012, 38(7):1227-1233
[12] 陈世明, 王培, 李海英, 赖强. 带强连通分支的多智能体系统可控包含控制. 控制理论与应用, 2017, 34(3):401-407(Chen S, Wang P, Li H, Lai Q. Controllable containment control of multi-agent systems with strongly connected sub-graph. Control Theory & Applications, 2017, 34(3):401-407)
[13] 盖彦荣, 陈阳舟, 宋学君, 齐耀辉. 有领导者线性多智能体系统一致性的分析与设计. 中南大学学报 (自然科学版), 2017, 48(3):735-741(Ge Y, Chen Y, Song X, Qi Y. Consensus analysis and design problem for leader-following linear multi-agent systems. Journal of Central South University (Science and Technology), 2017, 48(3):735-741)
[14] 谭拂晓, 关新平, 刘德荣. 非平衡拓扑结构的多智能体网络系统一致性协议. 控制理论与应用, 2009, 26(10):1087-1092(Tan F, Guan X, Liu D. Consensus protocol in networked multi-agent systems with non-balanced topology. Control Theory & Applications, 2009, 26(10):1087-1092)
[15] 席裕庚, 李晓丽. 多智能体系统一致性的递阶结构设计. 控制理论与应用, 2015, 32(9):1191-1199(Xi Y, Li X. Hierarchical structure design for multi-agent consensus. Control Theory & Applications, 2015, 32(9):1191-1199)
[16] Das A, Lewis F. Distributed adaptive control for synchronization of unknown nonlinear networked systems. Automatica, 2010, 46(12):2014-2021
[17] Ranjbar S, Shabaninia F, Nemati A, Stan S. A novel robust decentralized adaptive fuzzy control for swarm formation of multiagent systems. IEEE Transactions on Industrial Electronics, 2013, 59(8):3124-3134
[18] Arimoto S, Kawamura S, Miyazaki F. Bettering operation of robots by learning. J. Robotic Syst., 1984, 1(2):123-140
[19] Bristow D, Tharayil M, Alleyne A. A survey of iterative learning control. IEEE Control Syst. Mag., 2006, 26(3):96-114
[20] Meng D, Jia Y. Finite-time consensus for multi-agent systems via terminal feedback iterative learning. IET Control Theory and Applications, 2011, 5(18):2098-2110
[21] Meng D, Jia Y. Iterative learning approaches to design finitetime consensus protocols for multi-agent systems. Systems and Control Letters, 2012, 61(1):187-194
[22] Meng D, Jia Y, Du J, Yu F. Tracking control over a finite interval for multi-agent systems with a time-varying reference trajectory. Systems & Control Letters, 2012, (67):807-818
[23] Wang D. Convergence and robustness of discrete time nonlinear systems with iterative learning control. Automatica, 1998, 34(11):1445-1448
[24] Sun M, Wang D. Iterative learning control with initial rectifying action. Automatica, 2002, 38(7):1177-1182
[25] Li X, Chow T, Ho J, Zhang J. Iterative learning control with initial rectifying action for nonlinear continuous systems. IET Control Theory Appl., 2009, 3(1):49-55
[26] Xu J, Tan Y. A composite energy function-based learning control approach for nonlinear systems with time-varying parametric uncertainties. IEEE Trans. Autom. Control, 2002, 47(11):1940-1945
[27] Qu Z, Xu J. Asymptotic learning control for a class of cascaded nonlinear uncertain systems. IEEE Trans. Autom. Control, 2002, 47(8):1369-1376
[28] Chien C, Hsu C, Yao C. Fuzzy system-based adaptive iterative learning control for nonlinear plants with initial state errors. IEEE Trans. Fuzzy Syst., 2004, 12(5):724-732
[29] Xu J, Yan R. On initial conditions in iterative learning control. IEEE Trans. Autom. Control, 2005, 50(9):1349-1354
[30] Chi R, Hou Z, Xu J. Adaptive ILC for a class of discrete-time systems with iteration-varying trajectory and random initial condition. Automatica, 2008, 44(8):2207-2213
[31] 李金沙. 多智能体系统一致性学习协议的设计与分析. 西安电子科技大学, 2015(Li J. Design and analysis of consensus protocols for multi-agent systems by using learning control. Xi'an:Xidian University, 2015)
[32] 严求真, 孙明轩, 李鹤. 非参数不确定多智能体系统一致性误差跟踪学习控制. 控制理论与应用, 2016, 33(6):793-799(Yan Q, Sun M, Li H. Consensus-error-tracking learning control for nonparametric uncertain multi-agent systems. Control Theory & Applications, 2016, 33(6):793-799)

[1]刘志敏, 杜守强, 王瑞莹. 求解线性互补问题的Levenberg-Marquardt型算法[J]. 应用数学学报, 2018, 41(3): 403-419.
[2]刘金魁, 张春涛. 三项修正LS共轭梯度方法及其收敛性研究[J]. 应用数学学报, 2017, 40(6): 862-873.
[3]胡秀玲, 张鲁明. 空间四阶-时间分数阶扩散波方程的一个新的数值分析方法[J]. 应用数学学报, 2017, 40(4): 543-561.
[4]江羡珍, 简金宝. 一个自调节Polak-Ribière-Polyak型共轭梯度法[J]. 应用数学学报, 2017, 40(3): 449-460.
[5]邱德华, 陈平炎, 肖娟. END随机变量序列加权和的矩完全收敛性[J]. 应用数学学报, 2017, 40(3): 436-448.
[6]周辉, 王文, 周宗福. 具非线性收获项和S-型时滞Lasota-Wazewska模型的概周期解[J]. 应用数学学报, 2017, 40(3): 471-480.
[7]王亚飞, 杜江, 张忠占. 相依误差下部分函数型线性模型的估计[J]. 应用数学学报, 2017, 40(1): 49-65.
[8]席维鸽, 王力工. 有向图的拉普拉斯谱半径的几个上界[J]. 应用数学学报, 2016, 39(6): 801-810.
[9]唐国吉, 汪星, 叶明露. 混合变分不等式的一个投影型方法[J]. 应用数学学报, 2016, 39(4): 574-585.
[10]黄金超, 凌能祥. 一类改进的Cox模型参数的经验Bayes检验[J]. 应用数学学报, 2016, 39(4): 562-573.
[11]付宗魁, 吴群英. ρ-混合序列矩收敛的渐近性质[J]. 应用数学学报, 2016, 39(3): 452-462.
[12]原军, 刘爱霞. 局部内(外)半完全有向图可迹的充分条件[J]. 应用数学学报, 2016, 39(2): 200-212.
[13]董晓亮, 何郁波. 一类满足充分下降条件和自适应共轭性的修正THREECG方法[J]. 应用数学学报, 2016, 39(1): 58-70.
[14]丁睿, 朱征城, 沈铨. 一类时间二阶发展型变分不等式的EFG方法及其收敛性分析[J]. 应用数学学报, 2015, 38(5): 874-891.
[15]马燕, 裴艳波, 张海祥. 多类型的复发事件数据下一类混合模型[J]. 应用数学学报, 2015, 38(4): 660-672.



PDF全文下载地址:

http://123.57.41.99/jweb_yysxxb/CN/article/downloadArticleFile.do?attachType=PDF&id=14449
相关话题/应用数学 智能 控制 统计 设计