.png){kind=icon}
返回
Iterative learning consensus control for one-sided Lipschitz multi-agent systems
.png){kind=icon}
PRE
AI
DOI：10.1002/rnc.6943.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
By applying iterative learning control approach, the consensus is studied for multi-agent systems (MASs) with one-sided Lipschitz (OSL) nonlinearity. Firstly, the P-type and D-type learning schemes with initial state learning are introduced for such MASs. Then, utilizing the OSL and the quadratically inner-bounded constraints, the convergence conditions of the consensus algorithms are presented and analyzed under a directed communication graph. We show that both algorithms, on a fixed finite-time interval, can achieve perfect consensus tracking. Finally, the correctness of the obtained results is illustrated with simulation examples.
Keyword:
consensus
iterative learning control
multi-agent systems
one-sided Lipschitz
quadratically inner-bounded
期刊
IF:
3.2
论文数:
7.0K
被引数:
1.4W
机构
引用论文
.png){kind=icon}
分享收藏
Model Free Adaptive Iterative Learning Consensus Tracking Control for a Class of Nonlinear Multiagent Systems一类非线性多智能体系统的无模型自适应迭代学习一致性跟踪控制
PREAI
分享收藏
查看更多内容