Distributed adaptive asymptotically consensus tracking control of uncertain Euler-Lagrange systems under directed graph condition

被引:23
作者
Wang, Wei [1 ]
Wen, Changyun [2 ]
Huang, Jiangshuai [3 ,4 ]
Fan, Huijin [5 ]
机构
[1] Beihang Univ, Sch Automat Sci & Elect Engn, Beijing 100191, Peoples R China
[2] Nanyang Technol Univ, Sch Elect & Elect Engn, Nanyang Ave, Singapore 639798, Singapore
[3] Minist Educ, Key Lab Dependable Serv Comp Cyber Phys Soc, Beijing, Peoples R China
[4] Chongqing Univ, Sch Automat, Chongqing 400044, Peoples R China
[5] Huazhong Univ Sci & Technol, Sch Automat, Wuhan 430074, Hubei, Peoples R China
基金
中国国家自然科学基金;
关键词
Distributed adaptive control; Multiple Euler-Lagrange systems; Parametric uncertainties; Directed graph; Asymptotically consensus tracking; MULTIAGENT SYSTEMS; NONLINEAR-SYSTEMS; MOTION COORDINATION; REFERENCE VELOCITY; NETWORKS; AGENTS; TOPOLOGIES; FEEDBACK; SEEKING; LEADER;
D O I
10.1016/j.isatra.2017.06.017
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 paper, a backstepping based distributed adaptive control scheme is proposed for multiple uncertain Euler-Lagrange systems under directed graph condition. The common desired trajectory is allowed totally unknown by part of the subsystems and the linearly parameterized trajectory model assumed in currently available results is no longer needed. To compensate the effects due to unknown trajectory information, a smooth function of consensus errors and certain positive integrable functions are introduced in designing virtual control inputs. Besides, to overcome the difficulty of completely counteracting the coupling terms of distributed consensus errors and parameter estimation errors in the presence of asymmetric Laplacian matrix, extra information transmission of local parameter estimates are introduced among linked subsystem and adaptive gain technique is adopted to generate distributed torque inputs. It is shown that with the proposed distributed adaptive control scheme, global uniform boundedness of all the closed-loop signals and asymptotically output consensus tracking can be achieved. (C) 2017 ISA. Published by Elsevier Ltd. All rights reserved.
引用
收藏
页码:121 / 129
页数:9
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