Finite-Time Consensus for Linear Multi-Agent Systems Using Data-Driven Terminal ILC

被引：47

作者：

Bu, Xuhui ^{[1
]}

Zhu, Panpan ^{[1
]}

Hou, Zhongsheng ^{[2
,3
]}

Liang, Jiaqi ^{[1
]}

机构：

[1] Henan Polytech Univ, Sch Elect Engn & Automat, Jiaozuo 454003, Henan, Peoples R China

[2] Beijing Jiaotong Univ, Adv Control Syst Lab, Sch Elect & Informat Engn, Beijing 100044, Peoples R China

[3] Qingdao Univ, Sch Automat, Qingdao 266071, Peoples R China

来源：

IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS | 2020年 / 67卷 / 10期

基金：

中国国家自然科学基金;

关键词：

Multi-agent systems; Mathematical model; Consensus protocol; Convergence; Estimation; Parameter estimation; Terminal iterative learning control; finite-time consensus; data-driven control; multi-agent systems; ITERATIVE LEARNING CONTROL; TRACKING; DESIGN;

D O I：

10.1109/TCSII.2019.2944409

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

In this brief, the finite time consensus problem for a class of unknown linear multi-agent systems is considered. Firstly, a linear mapping relationship between the agent's terminal output and the control input along the iteration domain is established. Then, a novel distributed data-driven iterative learning consensus protocol is constructed only using the I/O data of each agent and its neighbors. Meanwhile, a convergence condition that does not depend on model information is derived for the multi-agent system. It is shown that the proposed protocol can guarantee that all agents achieve the finite-time consensus objective. Finally, an example of numerical simulation is given to verify the effectiveness of the proposed design.

引用

页码：2029 / 2033

页数：5

共 28 条

[1] Iterative learning control: Brief survey and categorization [J].

Ahn, Hyo-Sung ;

Chen, YangQuan ;

Moore, Kevin L. .

IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART C-APPLICATIONS AND REVIEWS, 2007, 37 (06) :1099-1121

[2] BETTERING OPERATION OF ROBOTS BY LEARNING [J].

ARIMOTO, S ;

KAWAMURA, S ;

MIYAZAKI, F .

JOURNAL OF ROBOTIC SYSTEMS, 1984, 1 (02) :123-140

[3] Data-Driven Multiagent Systems Consensus Tracking Using Model Free Adaptive Control [J].

Bu, Xuhui ;

Hou, Zhongsheng ;

Zhang, Hongwei .

IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2018, 29 (05) :1514-1524

[4] An Overview of Recent Progress in the Study of Distributed Multi-Agent Coordination [J].

Cao, Yongcan ;

Yu, Wenwu ;

Ren, Wei ;

Chen, Guanrong .

IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2013, 9 (01) :427-438

[5] Enhanced Data-Driven Optimal Terminal ILC Using Current Iteration Control Knowledge [J].

Chi, Ronghu ;

Hou, Zhongsheng ;

Jin, Shangtai ;

Wang, Danwei ;

Chien, Chiang-Ju .

IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2015, 26 (11) :2939-2948

[6] Data-driven optimal terminal iterative learning control [J].

Chi, Ronghu ;

Wang, Danwei ;

Hou, Zhongsheng ;

Jin, Shangtai .

JOURNAL OF PROCESS CONTROL, 2012, 22 (10) :2026-2037

[7] Distributed adaptive fault-tolerant control approach to cooperative output regulation for linear multi-agent systems [J].

Deng, Chao ;

Yang, Guang-Hong .

AUTOMATICA, 2019, 103 :62-68

[8] Distributed Adaptive Fuzzy Control For Nonlinear Multiagent Systems Under Directed Graphs [J].

Deng, Chao ;

Yang, Guang-Hong .

IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2018, 26 (03) :1356-1366

[9] Consensus of Linear Multiagent Systems With Actuator Saturation and External Disturbances [J].

Deng, Chao ;

Yang, Guang-Hong .

IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS, 2017, 64 (03) :284-288

[10] Finite-Time Consensus for Second-Order Multi-Agent Systems With Input Saturation [J].

Fu, Junjie ;

Wen, Guanghui ;

Yu, Wenwu ;

Ding, Zhengtao .

IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS, 2018, 65 (11) :1758-1762

← 1 2 3 →