Distributed Dual-Layer Adaptive Event-Triggered Formation Tracking for Quadrotor UAVs

Achieving resource-efficient robust tracking is critical for micro aerial robotics subject to external disturbances. In this paper, a novel distributed dual-layer adaptive event-triggered controller is proposed for cooperative formation tracking under unknown disturbances. Two different triggering sequences are designed to determine the appropriate instants for communication and control updates, thus greatly reducing the update frequency of the controller and communication consumption. Moreover, adaptive event-triggered conditions with heterogeneous parameters are well-desigeed to cope with unknown disturbances, while improving the flexibility of parameter selection and excluding Zeno behavior. By employing Lyapunov theory, new sufficient conditions for ensuring the feasibility of the proposed algorithm are rigorously derived to eliminate the conservatism. The performance of the proposed algorithm is illustrated through numerical validations of co-operative formation tracking under cluttered nonlinear disturbances, and a detailed comparison with existing algorithms is made to fully demonstrate the robustness and advantage of the proposed algorithm.