Collaborative Optimal Formation Control for Heterogeneous Multi-Agent Systems

Area of Science:

• Robotics and Control Systems
• Multi-Agent Systems
• Aerospace Engineering

Background:

• Cooperative formation control is crucial for heterogeneous multi-agent systems operating in complex environments.
• Existing methods may face challenges in achieving efficient and rapid formation for air-ground teams.

Purpose of the Study:

• To develop and analyze a distributed optimal control strategy for cooperative formation of unmanned aerial vehicles (UAVs) and unmanned ground vehicles (UGVs).
• To enhance the speed and convergence of formation maneuvers in air-ground cooperative systems.

Main Methods:

• Distributed optimal control applied to a heterogeneous air-ground system (UAV and UGV).
• Design of a distributed optimal formation control protocol.
• Stability verification using graph theory.
• Analysis of a cooperative optimal formation control protocol using block Kronecker product and matrix transformation theory.

Main Results:

• The proposed distributed optimal control method effectively manages cooperative formation for UAVs and UGVs.
• Stability of the designed protocols was rigorously verified through theoretical analysis.
• Simulation results demonstrate a significant reduction in formation time and accelerated convergence speed compared to baseline methods.

Conclusions:

• The integration of optimal control theory into formation protocols significantly improves the performance of heterogeneous air-ground multi-agent systems.
• The developed distributed optimal control strategy offers a robust and efficient solution for cooperative formation tasks.
• This research contributes to advancements in autonomous systems coordination for complex operational scenarios.