Time-Varying Formation Tracking for UAV Swarm Systems With Switching Directed Topologies

Area of Science:

• Robotics
• Control Systems Engineering
• Aerospace Engineering

Background:

• Cooperative control of multi-agent systems, particularly unmanned aerial vehicles (UAVs), is crucial for complex missions.
• Existing formation tracking methods often struggle with dynamic network topologies and limited information dissemination.
• Time-varying formation tracking (TVFT) presents unique challenges due to the constantly changing spatial arrangements and leader-follower dynamics.

Purpose of the Study:

• To develop a robust control protocol for UAV swarms to achieve time-varying formation tracking.
• To address challenges posed by switching and directed interaction topologies in UAV communication networks.
• To enable follower UAVs to accurately track a leader UAV while maintaining a specified time-varying formation.

Main Methods:

• A novel Time-Varying Formation Tracking (TVFT) control protocol is designed using local neighboring information.
• An algorithm involving four distinct steps is proposed for the systematic design of the TVFT protocol.
• The stability and feasibility of the TVFT protocol are mathematically proven under specific conditions related to topology switching and system parameters.

Main Results:

• The proposed TVFT control protocol enables UAV swarms to achieve desired formations despite switching communication topologies.
• The protocol ensures successful formation tracking when the dwell time of switching topologies exceeds a defined threshold and feasibility conditions are met.
• A practical quadrotor UAV formation control platform utilizing ultrawideband positioning technology was developed and validated.

Conclusions:

• The developed TVFT control protocol is effective for UAV swarms operating with dynamic and directed interaction networks.
• The protocol successfully addresses the target enclosing problem, demonstrating its applicability in real-world scenarios.
• Experimental validation with a quadrotor UAV swarm confirms the theoretical findings and the practical effectiveness of the proposed control strategy.