Distributed Robustness-and-Safety-Critical Formation Control of Autonomous Aerial Vehicles

This paper addresses the robustness-and-safety-critical formation control of quadrotor unmanned aerial vehicles (UAVs) that aims at coordinating the followers tracking a dynamic leader while maintaining a preassigned shape. Specifically, a distributed optimization control strategy consisting of a position controller and an attitude controller is proposed. First, a data-based learning estimator is utilized to approximate the dynamics uncertainty, where the approximation error is compensated by a dynamics estimator. Next, a fully distributed position controller that involves local position and velocity exchange with its neighbors is designed. For the sake of avoiding the collision with static obstacles and dynamic UAVs, a quadratic programming optimization is exploited. Then, by following the cascade-estimator development, a robust learning attitude controller is provided for the attitude-loop tracking, where a quadratic programming optimization is also implemented to ensure the safe orientation. Stability analysis demonstrates the asymptotic stability of the overall closed-loop system without violating the safety constraints. Finally, the proposed control strategy is verified and assessed by numerical simulations and real-world flight experiments.