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Distributed Consensus Control for Discrete-Time T-S Fuzzy Multiple-Agent Systems Based on an Unknown Input Observer.

Xufeng Ling1, Haichuan Xu2, Weijie Weng3

  • 1School of Artificial Intelligence, Shanghai Normal University Tianhua College, Shanghai 201815, China.

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Summary
This summary is machine-generated.

This study develops an unknown input observer (UIO) for Takagi-Sugeno fuzzy multiple-agent systems (MASs) to achieve consensus. The proposed method enables agents to reach agreement by estimating system states and unknown inputs.

Keywords:
T–S fuzzy systemsdistributed consensusmultiple-agent systemsunknown input observerzonotope theory

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Area of Science:

  • Control Systems Engineering
  • Artificial Intelligence
  • Systems Theory

Background:

  • Consensus is crucial for coordinated behavior in multiple-agent systems (MASs).
  • Takagi-Sugeno (T-S) fuzzy models are widely used to represent nonlinear systems.
  • Unknown inputs pose significant challenges in observer design and system control.

Purpose of the Study:

  • To address the consensus problem in T-S fuzzy MASs with unknown inputs.
  • To design an unknown input observer (UIO) for state and unknown input estimation.
  • To develop a distributed control protocol for achieving consensus.

Main Methods:

  • Utilizing zonotope theory for state interval estimation.
  • Establishing an algebraic relationship for UIO construction.
  • Developing a distributed control protocol based on UIO estimations.

Main Results:

  • An effective UIO is designed to estimate system states and unknown inputs.
  • A distributed control protocol is developed using the UIO.
  • The proposed control protocol ensures asymptotic consensus in T-S fuzzy MASs.

Conclusions:

  • The proposed UIO-based approach effectively solves the consensus problem for T-S fuzzy MASs with unknown inputs.
  • The method is validated through simulation examples, demonstrating its practical applicability.