Distributed Model Predictive Control with Adaptive Safety Zones for Multi-Fleet Drone Operations

The article presents a novel approach to distributed model predictive control (DMPC) for autonomous drone swarms, introducing adaptive safety zones that adjust based on drone speed, enhancing airspace efficiency in high-density environments. It details a centralized MPC formulation and a distributed variant that accommodates mixed fleets, demonstrating feasibility up to geometric packing limits and establishing Lyapunov stability under specific conditions. This adaptive framework significantly increases the feasible drone count and reduces traversal times in constrained passages, offering practical benefits for real-world deployment of drone operations in crowded airspaces.