Distributed MPC for Connectivity-Constrained Fixed-Wing Aerial Swarms

This paper addresses the problem of maintaining communication connectivity within a swarm of fixed-wing aerial vehicles operating under dynamic and range constraints. Fixed-wing platforms, while offering superior endurance and coverage capabilities compared to rotary-wing ones, pose additional challenges due to their nonholonomic dynamics and limited maneuverability. To tackle these challenges, we propose both centralized and distributed model predictive control formulations that explicitly integrate the algebraic connectivity of the inter-vehicle communication graph into the control framework. The resulting controllers allow each vehicle to anticipate connectivity degradation and adjust its trajectory proactively while pursuing observation and coverage objectives. The proposed approaches are benchmarked against heuristic and convex optimization-based controllers in a simulated multi-target surveillance scenario. Simulation results demonstrate that the distributed model predictive control scheme achieves comparable mission performance to centralized schemes while maintaining consistent network connectivity and robustness to target switches. These findings highlight the potential of predictive, connectivity-aware control for enabling scalable and resilient coordination of fixed-wing swarms in real-world applications.