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Distributed H∞ consensus of heterogeneous multi-agent systems with nonconvex constraints.

Yinsen Zhang1, Xue Li2, LuLu Wang1

  • 1School of Microelectronics and Communication Engineering, Chongqing University, Chongqing 400044, China.

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This study addresses distributed H∞ consensus for multi-agent systems with nonconvex constraints. It achieves consensus with H∞ performance despite disturbances and constraints using system transformation and H∞ control theory.

Keywords:
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Area of Science:

  • Control Theory
  • Systems Engineering
  • Robotics

Background:

  • Investigating distributed H∞ consensus for heterogeneous multi-agent systems presents challenges due to nonconvex constraints and external disturbances.
  • Existing methods may struggle to simultaneously handle these complex system dynamics and performance requirements.

Purpose of the Study:

  • To develop a novel approach for achieving distributed H∞ consensus in heterogeneous multi-agent systems.
  • To ensure consensus is reached while adhering to nonconvex input constraints and maintaining a specified H∞ performance level.
  • To address the challenge of disturbances in conjunction with nonconvex constraints.

Main Methods:

  • The core methodology involves transforming the original complex system into a reduced-order system.
  • H∞ control theory is applied to the transformed system to guarantee consensus and performance.
  • The approach explicitly accounts for and manages nonconvex constraints on agent inputs.

Main Results:

  • The proposed method successfully achieves distributed H∞ consensus for the heterogeneous multi-agent systems.
  • The system demonstrates the desired H∞ performance under the specified nonconvex constraints.
  • The effectiveness of the approach in handling disturbances is validated.

Conclusions:

  • The study presents a viable method for distributed H∞ consensus in systems with nonconvex constraints and disturbances.
  • The transformation to a reduced-order system combined with H∞ control is an effective strategy.
  • Numerical simulations confirm the theoretical findings and the practical applicability of the method.