Optimizing Multi-Agent Systems With Uncertain Dynamics: A Finite-Time Adaptive Distributed Approach

Jiayi Lei, Yuan Xin Li, Choon Ki Ahn

Research output: Contribution to journalArticlepeer-review


The topic of this study is adaptive distributed finite-time (FT) optimization of uncertain nonlinear high-order multi-agent systems (MASs) with disturbances. The proposed two-stage framework consists of an optimal FT estimator and an adaptive FT tracking controller. First, the estimator drives the optimization variables towards the optimal solution. In contrast to existing optimization control studies, high-order MASs subject to unknown dynamics are studied in this case. Second, by using the output of the estimator as a reference signal, the tracking controller allows all agents to approach the optimal point. The use of a command filter avoids the problem of discontinuous gradient functions, while it is possible to handle unknown nonlinear functions using fuzzy logic systems (FLSs). We prove, based on the FT stability criterion and convex optimization theory, that the proposed strategy minimizes the total objective function and results in a closed-loop system with bounded signals and FT convergence to the optimal solution. Finally, through a simulation example, the developed approach is verified.

Original languageEnglish
Article number10337743
Pages (from-to)865-874
Number of pages10
JournalIEEE Transactions on Signal and Information Processing over Networks
Publication statusPublished - 2023

Bibliographical note

Publisher Copyright:
© 2015 IEEE.


  • command filter
  • Distributed finite-time (FT) optimization
  • fuzzy logic system (FLS)
  • uncertain high-order multi-agent system (MAS)

ASJC Scopus subject areas

  • Signal Processing
  • Information Systems
  • Computer Networks and Communications


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