无人机自主着陆纵向控制律设计

针对无人机的自主高精度定点着陆,应用自适应内模控制(AIMC)原理设计了自主着陆纵向飞行控制律。以轮式无人机为平台,将纵向非线性模型解耦并线性化。然后,以地速和下沉率为控制目标,应用AIMC理论设计了纵向飞行控制律。通过对AIMC滤波参数进行自调整改善了系统的动态特性,基于对模型的辨识增强了系统的鲁棒性。在顺逆风6m/s的条件下对AIMC系统进行了数字仿真,结果显示其落点精度达到前后向30 m范围内。与传统内模控制(IMC)系统相比,提出的自适应内模控制(AIMC)系统在动态性能和落点精度等方面均有明显提高。最后,搭建了半物理测试平台,通过半物理仿真测试复现了系统数字仿真结果,验证了系统功能的完整性和协调性。

Design of longitudinal control law for small fixed-wing UAV during auto landing

For the auto landing precisely of an Unmanned Aerial Vehicle(UAV), the longitudinal control law for the auto landing of the UVA was designed based on Adaptive Internal Model Control (AIMC) principle. By taking a small wheeled UVA as a working platform, the longitudinal nonlinear model was decoupled and linearized. Then, the ground speed and sink rate were selected as control targets and longitudinal control law was designed based on the AIMC and applied to control system design. The filter parameter was adjusted to improve the dynamic characteristics of the system and the model was identified to enhanced the robustness of the system. The AIMC system was simulated digitally under the conditions of ownwind or headwind in a speed of 6 m/s, and the results show that the landing precision of system is in a scope of 30 m for forward or backward directions. Finally, a hardware test platform was established to verify the simulation results and the hardware-in-loop-simulation (HILS) proves the harmony and integrality of the system.