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Area of Science:

  • Robotics
  • Control Systems Engineering
  • Distributed Systems

Background:

  • Multi-agent systems (MAS) present challenges in coordinated control due to nonlinear dynamics and uncertainties.
  • Aerial robots require robust formation control algorithms for complex missions.
  • Existing control methods may not adequately address nonlinear dynamics and parametric uncertainties in MAS.

Purpose of the Study:

  • To propose a novel distributed formation control algorithm for nonlinear uncertain multi-agent systems.
  • To ensure robust and stable control for a team of aerial robots operating with nonlinear dynamics.
  • To analyze the algorithm's performance under various communication network configurations and external disturbances.

Main Methods:

  • Development of a distributed control algorithm based on a nonlinear H∞ framework.
  • Formulation of local control laws utilizing agents' information and neighbor data.
  • Analytical proof of system stability.
  • Numerical simulations to evaluate performance against disturbances and uncertainties.

Main Results:

  • The proposed algorithm demonstrates robust performance in the presence of external disturbances and bounded uncertainties.
  • Simulation results verify the stability and effectiveness of the distributed control laws.
  • Analysis of communication network configurations shows their impact on overall system performance.
  • Calculated Integral Squared Error (ISE) and Integral Absolute Deviation from Unity (IADU) indexes confirm the algorithm's superiority over independent agent control.

Conclusions:

  • The novel distributed formation control algorithm is effective for nonlinear uncertain multi-agent systems, particularly for aerial robots.
  • The algorithm ensures robust stability and performance, even with bounded uncertainties and external disturbances.
  • Communication network topology significantly influences the performance of distributed formation control in multi-agent systems.