Distributed optimization for consensus performance of delayed fractional-order double-integrator multi-agent systems

被引：6

作者：

Liu, Jun ^{[1
,6
]}

Zhou, Nan ^{[2
,6
]}

Qin, Kaiyu ^{[3
]}

Chen, Badong ^{[4
]}

Wu, Yonghong ^{[5
]}

Choi, Kup-Sze ^{[6
]}

机构：

[1] Chengdu Univ Informat Technol, Sch Automat, Chengdu, Peoples R China

[2] Chengdu Univ, Sch Elect Informat & Elect Engn, Chengdu, Peoples R China

[3] Univ Elect Sci & Technol China, Sch Aeronaut & Astronaut, Chengdu, Peoples R China

[4] Xi An Jiao Tong Univ, Inst Artificial Intelligence & Robot, Xian, Peoples R China

[5] Wuhan Univ Technol, Sch Sci, Wuhan, Peoples R China

[6] Hong Kong Polytech Univ, Ctr Smart Hlth, Hong Kong, Peoples R China

来源：

NEUROCOMPUTING | 2023年 / 522卷

基金：

中国国家自然科学基金;

关键词：

Distributed optimization; Consensus; Fractional-order; Double-integrator; Multi-agent systems; Network topology; State-fractional-order-derivative feedback; Time-delays;

D O I：

10.1016/j.neucom.2022.12.005

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper addresses distributed optimization problems concerning consensus in delayed fractional -order double-integrator multi-agent systems (FDMSs). To start with, an optimized distributed protocol with state-fractional-order-derivative feedback (SF) is presented for delayed FDMSs. Then, the consensus problems are studied for the two kinds of delayed FDMSs with SF in the presence of symmetric time -delays over undirected network topology and asymmetric time-delays over directed network topology. Next, by the means of graph theory, matrix theory and frequency-domain analysis method, the sufficient conditions to guarantee consensus of delayed FDMSs with SF are derived. Compared to the traditional distributed protocol without SF, the proposed distributed optimization protocol with SF are taken into account to enable better consensus performance in delayed FDMSs with SF. Finally, numerical experi-ments are carried out to verify the feasibility of our theoretical results.(c) 2022 Elsevier B.V. All rights reserved.

引用

页码：105 / 115

页数：11

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