基于预设性能的四旋翼无人机编队安全控制

针对四旋翼无人机编队系统存在模型不确定性、未知外部干扰与内部碰撞等问题，提出一种基于预设性能的安全控制方法。首先使用预设性能函数结合误差转换方法，将防止内部碰撞的不等式约束问题转换为无约束问题。同时针对模型中的不确定项，使用神经网络进行逼近；针对神经网络逼近误差与未知外部干扰组成的复合干扰，使用非线性干扰观测器进行估计，并分别设计位置与姿态子系统控制器，避免了编队内四旋翼无人机的碰撞。然后借助Lyapunov方法证明了闭环系统所有信号的收敛性。最后通过数值仿真验证了所提控制方法的有效性。

Safety formation control of quadrotor UAVs based on prescribed performance

Quadrotor UAVs formation suffers from the problems of model uncertainties, unknown external disturbances and collision between UAVs. In this paper, a safety control scheme is proposed based on prescribed performance. Firstly, the inequality constraint problem which will prevent collision between UAVs is transformed into the unconstrained problem according to the Prescribed Performance Function (PPF) and the error transfer function. To tackle model uncertainty, the neural network is used for approximation. The unknown approximation errors and the unknown external disturbances are treated as a compound disturbance, which is then estimated by the nonlinear disturbance observer. By using the transformed tracking errors and the values obtained by the observer, controllers are designed for the position and attitude subsystems, thus the collision between quadrotor UAVs is avoided. Then, the convergence of all the closed-loop system signals under the designed controller is proved by the Lyapunov method. Finally, numerical simulations verify the effectiveness of the proposed scheme.