Distributed adaptive output consensus control of second-order systems containing unknown non-linear control gains

被引:15
作者
Wang, Gang [1 ]
Wang, Chaoli [2 ]
Du, Qinghui [3 ]
Cai, Xuan [2 ]
机构
[1] Univ Shanghai Sci & Technol, Business Sch Syst Anal & Integrat, Shanghai, Peoples R China
[2] Univ Shanghai Sci & Technol, Dept Control Sci & Engn, Shanghai, Peoples R China
[3] Luoyang Normal Univ, Dept Math, Luoyang, Peoples R China
关键词
Output consensus; distributed control; adaptive control; Fourier series; unknown control gains; COOPERATIVE TRACKING CONTROL; MULTIAGENT SYSTEMS; MOTION COORDINATION; REFERENCE VELOCITY; NEURAL-NETWORKS; FEEDBACK; UNCERTAINTIES; SYNCHRONIZATION; DESIGN;
D O I
10.1080/00207721.2016.1139760
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, we address the output consensus problem of tracking a desired trajectory for a group of second-order agents on a directed graph with a fixed topology. Each agent is modelled by a second-order non-linear system with unknown non-linear dynamics and unknown non-linear control gains. Only a subset of the agents is given access to the desired trajectory information directly. A distributed adaptive consensus protocol driving all agents to track the desired trajectory is presented using the backstepping technique and approximation technique of Fourier series (FSs). The FS structure is taken not only for tracking the non-linear dynamics but also the unknown portion in the controller design procedure, which can avoid virtual controllers containing the uncertain terms. Stability analysis and parameter convergence of the proposed algorithm are conducted based on the Lyapunov theory and the algebraic graph theory. It is also demonstrated that arbitrary small tracking errors can be achieved by appropriately choosing design parameters. Though the proposed work is applicable for second-order non-linear systems containing unknown non-linear control gains, the proposed controller design can be easily extended to higher-order non-linear systems containing unknown non-linear control gains. Simulation results show the effectiveness of the proposed schemes.
引用
收藏
页码:3350 / 3363
页数:14
相关论文
共 41 条
[1]  
[Anonymous], 2014, IEEE Transactions on Automatic Control
[2]  
[Anonymous], 1995, NONLINEAR ADAPTIVE C
[3]   Adaptive design for reference velocity recovery in motion coordination [J].
Bai, He ;
Arcak, Murat ;
Wen, John T. .
SYSTEMS & CONTROL LETTERS, 2008, 57 (08) :602-610
[4]   Adaptive motion coordination: Using relative velocity feedback to track a reference velocity [J].
Bai, He ;
Arcak, Murat ;
Wen, John T. .
AUTOMATICA, 2009, 45 (04) :1020-1025
[5]   Neural-Network-Based Adaptive Leader-Following Control for Multiagent Systems with Uncertainties [J].
Cheng, Long ;
Hou, Zeng-Guang ;
Tan, Min ;
Lin, Yingzi ;
Zhang, Wenjun .
IEEE TRANSACTIONS ON NEURAL NETWORKS, 2010, 21 (08) :1351-1358
[6]   Comparison of adaptive methods for function estimation from samples [J].
Cherkassky, V ;
Gehring, D .
IEEE TRANSACTIONS ON NEURAL NETWORKS, 1996, 7 (04) :969-984
[7]   Cooperative adaptive control for synchronization of second-order systems with unknown nonlinearities [J].
Das, Abhijit ;
Lewis, Frank L. .
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL, 2011, 21 (13) :1509-1524
[8]   Distributed adaptive control for synchronization of unknown nonlinear networked systems [J].
Das, Abhijit ;
Lewis, Frank L. .
AUTOMATICA, 2010, 46 (12) :2014-2021
[9]   Neuro-adaptive cooperative tracking control of unknown higher-order affine nonlinear systems [J].
El-Ferik, Sami ;
Qureshi, Aminuddin ;
Lewis, Frank L. .
AUTOMATICA, 2014, 50 (03) :798-808
[10]   Information flow and cooperative control of vehicle formations [J].
Fax, JA ;
Murray, RM .
IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 2004, 49 (09) :1465-1476