Adaptive Fuzzy Distributed Optimization for Uncertain Nonlinear Multiagent Systems

Yukan Zheng, Yuan Xin Li, Choon Ki Ahn

Research output: Contribution to journalArticlepeer-review

Abstract

The adaptive fuzzy distributed optimization problem of nonlinear multi-agent systems (MASs) with unknown nonlinearities and uncertain disturbances is explored in this paper. The unknown nonlinearities in the system model are determined by incorporating fuzzy-logic systems. Rather than using the existing known gradient values of local objective functions, this paper further takes into account the measured gradient values that are based on the output information. The bounded estimation method and well-defined smooth functions are used to account for the effects of uncertainties. To ensure that the output can asymptotically converge to the optimal solution, a new adaptive fuzzy distributed optimization controller is proposed using the Lyapunov function method and the adaptive backstepping technique. To demonstrate the effectiveness of the developed distributed optimization technique, two practical examples are used.

Original languageEnglish
Pages (from-to)1-10
Number of pages10
JournalIEEE Transactions on Fuzzy Systems
DOIs
Publication statusAccepted/In press - 2023

Bibliographical note

Publisher Copyright:
IEEE

Keywords

  • Adaptive systems
  • Backstepping
  • Distributed optimization
  • Fuzzy logic
  • Multi-agent systems
  • Optimization
  • Radio frequency
  • Symmetric matrices
  • adaptive backstepping design
  • fuzzy logic system
  • uncertain multi-agent system

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computational Theory and Mathematics
  • Artificial Intelligence
  • Applied Mathematics

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