Distributed Near-Optimal Consensus of Double-Integrator Multi-Agent Systems With Input Constraints

被引：1

作者：

Deng, Qingyun ^{[1
]}

Zhang, Yinyan ^{[1
]}

机构：

[1] Jinan Univ, Coll Cyber Secur, Guangzhou, Peoples R China

来源：

2021 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN) | 2021年

关键词：

consensus; optimal control; double-integrator dynamics; multi-agent system; SWITCHING TOPOLOGY;

D O I：

10.1109/IJCNN52387.2021.9533377

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this paper, we propose novel distributed near-optimal consensus protocols for input-constrained double-integrator multi-agent systems with an undirected connected communication topology. The design of the consensus protocols is based on the optimization of an integral-type performance index. By using the Taylor expansion and projection neural networks, we realize the optimization of the performance indices subject to the input constraints of the agents. The performance of the proposed consensus protocols is demonstrated via computer simulations.

引用

页数：6

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