Backstepping-Based Adaptive Formation Control of Quadrotor UAVs with Multiple Disturbances

This paper investigates the problem of multiple unmanned aerial vehicles (UAVs) formation control subject to unknown external disturbances. The dynamics of UAVs are described by three-dimensional second-order nonlinear models, and the unknown nonlinear functions are approximated using the radial basis function neural networks. The disturbance filters are designed to convert the disturbance rejection problem into an adaptive tracking problem, then the values of the unknown disturbances are estimated based on the adaptive backstepping method, and the effect of the disturbances is eliminated. Lyapunov stability analysis supports the global uniform boundedness of all closed-loop signals. Finally, the simulation results prove the effectiveness of the proposed solution.