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

  • Jun Liu
  • , Nan Zhou
  • , Kaiyu Qin
  • , Badong Chen
  • , Yonghong Wu
  • , Kup Sze Choi
  • Chengdu University of Information Technology
  • Hong Kong Polytechnic University
  • Chengdu University
  • University of Electronic Science and Technology of China
  • Wuhan University of Technology

Research output: Contribution to journalArticlepeer-review

17 Scopus citations

Abstract

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 experiments are carried out to verify the feasibility of our theoretical results.

Original languageEnglish
Pages (from-to)105-115
Number of pages11
JournalNeurocomputing
Volume522
DOIs
StatePublished - 14 Feb 2023

Keywords

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

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