Distributed MPC-Based Trajectory Tracking Control for a Multi-Quadrotor UAV Slung Load System

This paper examines the issue of collision-avoidance trajectory tracking control in a multi-quadrotor unmanned aerial vehicle (UAV) slung load system, with particular emphasis on the scenario where the reference trajectory is unreachable. The challenge of tracking an unreachable reference trajectory is effectively addressed by integrating a trajectory planner and a trajectory tracking controller within a unified distributed model predictive control (DMPC) framework. Moreover, the nonlinear system is linearized using the first-order Taylor approximation, significantly simplifying the computation in DMPC. To ensure collision avoidance with both dynamic and static obstacles, the MINVO basis is employed to calculate the minimum volume of the exterior polyhedral approximation of the obstacles' trajectories, which is significantly smaller than that achieved using the B-spline or Bernstein bases typically utilized in the planning literature. Simulation experiments involving four UAVs, one payload, two static obstacles, and one dynamic obstacle are conducted to evaluate the effectiveness of the proposed DMPC method.