Distributed Control for Coordinated Tracking of Fixed-Wing Unmanned Aerial Vehicles under Model Uncertainty and Disturbances

Abstract

In this paper, we consider a control problem where a group of fixed-wing unmanned aerial vehicles (UAVs) with uncertain dynamics tracks the target vehicle cooperatively in the case of external disturbance. Based on the Gaussian process regression, a data-driven model is established, whose uniform error is bounded with probability. Then a learning-based consensus protocol for multi-UAVs is designed. The stability of the system is proven via Lyapunov function, and the tracking error is guaranteed to be bounded with a high probability. Finally, the effectiveness of the proposed method is shown in the numerical simulation.

Keywords

• gaussian process regression
• uniform bound
• fixed-wing UAV
• consensus protocol