论文标题
轨迹优化和NMPC跟踪，用于固定翼无人机在深摊中，鲈鱼着陆
Trajectory Optimization and NMPC Tracking for a Fixed Wing UAV in Deep Stall with Perch Landing
论文作者
论文摘要
本文为固定翼无人机（无人驾驶飞机）提供了一种新型的恢复技术：i）我们提出了登陆无人机的轨迹生成，首先它通过深度停滞来降低其高度，然后在恢复网上栖息，然后栖息在恢复网络上，ii），我们设计了NMPC（非线性模型预测控制）的轨道构造，以实现终止控制范围，以终止控制范围。与名义净恢复程序相比，该技术大大减少了无人机的着陆时间和最终空速。各种风条件的仿真结果证明了这个想法的可行性。
This paper presents a novel recovery technique for a fixed-wing UAV (Unmanned Aerial Vehicle) based on constrained optimization: i) we propose a trajectory generation for landing the UAV where it first reduces its altitude by deep stalling, then perches on a recovery net, ii) we design an NMPC (Nonlinear Model Predictive Control) tracking controller with terminal constraints for the optimal generated trajectory under disturbances. Compared to nominal net recovery procedures, this technique greatly reduces the landing time and the final airspeed of the UAV. Simulation results for various wind conditions demonstrate the feasibility of the idea.
