Consensus control for directed networks with multiple higher-order discrete dynamic agents: An ILC-based approach

被引：0

作者：

Meng, Deyuan ^{[1
]}

Jia, Yingmin ^{[1
]}

Du, Junping ^{[2
]}

Yu, Fashan ^{[3
]}

机构：

[1] Beihang Univ BUAA, Res Div 7, Beijing 100191, Peoples R China

[2] Beijing Univ Posts & Telecommun, Sch Comp Sci & Technol, Beijing 100876, Peoples R China

[3] Henan Polytechn Univ, Sch Elect Engn & Automat, Henan 454000, Peoples R China

来源：

2012 IEEE 51ST ANNUAL CONFERENCE ON DECISION AND CONTROL (CDC) | 2012年

关键词：

Iterative learning control; consensus control; monotonic convergence; robustness; directed networks; multi-agent systems; ITERATIVE LEARNING CONTROL; FINITE-TIME CONSENSUS; MULTIAGENT SYSTEMS; INTERVAL;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper demonstrates that the idea of iterative learning control (ILC) can be applied to deal with the consensus problems for multi-agent systems. All agents are considered in directed networks and with higher-order discrete dynamics. It is shown that the multi-agent system can be enabled to achieve consensus at any desired state, and its process can be guaranteed to converge monotonically by selecting learning parameters appropriately. Furthermore, the ILC-based consensus protocols can provide sufficient robustness against network uncertainties. Simulation results are provided to verify the effectiveness of our theoretical study.

引用

页码：4666 / 4671

页数：6