Resilient Collision-Free Distributed Optimal Coordination for Multiple Euler-Lagrangian Systems Under Unreliable...

Area of Science:

• Robotics
• Control Systems
• Networked Systems

Background:

• Distributed optimal coordination (DOC) is crucial for multi-agent systems.
• Unreliable communication topologies, due to network issues or cyber attacks, pose significant challenges to collision avoidance.
• Existing methods may not adequately address resilience under intermittent communication.

Purpose of the Study:

• To develop a resilient collision avoidance distributed optimal coordination (DOC) strategy for multiple Euler-Lagrangian (EL) systems.
• To ensure reliable collision avoidance and system convergence under unreliable communication conditions.
• To enhance the robustness of multi-agent coordination against network disruptions and cyber threats.

Main Methods:

• Redesigning a barrier function for collision avoidance.
• Proposing a communication-based distributed collision avoidance algorithm.
• Introducing a resilient DOC strategy using real-time position-based gradient, a coordinator, and an adaptive tracking controller.

Main Results:

• The proposed DOC strategy guarantees collision avoidance for multiple EL systems.
• The strategy ensures system convergence even with unreliable communication topologies.
• Lyapunov method and boundedness analysis confirm the effectiveness and resilience of the approach.

Conclusions:

• The developed resilient collision avoidance DOC strategy effectively manages multi-agent systems under adverse communication conditions.
• The approach provides a robust solution for collision avoidance in networked systems facing communication uncertainties.
• Simulation results validate the practical applicability and performance of the proposed strategy.