孪生场景驱动的固定翼无人机进场自主着陆控制  

Twin-scenario driven autolanding control for fixed-wing UAVs

作　　者：马国庆 田秋扬 朱波 胡天江 MA Guo-qing;TIAN Qiu-yang;ZHU Bo;HU Tian-jiang(School of Aeronautics and Astronautics,Sun Yat-sen University,Shenzhen Guangdong 518107,China;School of Artificial Intelligence,Sun Yat-sen University,Zhuhai Guangdong 519082,China)

机构地区：[1]中山大学航空航天学院,广东深圳518107 [2]中山大学人工智能学院,广东珠海519082

出　　处：《控制理论与应用》2024年第9期1664-1675,共12页Control Theory & Applications

基　　金：国家自然科学基金项目(61973327)资助.

摘　　要：本文针对固定翼无人机着陆过程中低空风扰难建模等实际问题,提出孪生场景驱动的自主着陆飞行控制优化方案.首先,引入孪生技术,构建高保真场景模拟系统,采集无人机多架次安全着陆飞行数据;进而,挖掘历史安全着陆飞行经验,设计轨迹跟踪学习控制算法来抵抗低空风扰影响,并设计期望着陆轨迹在线调整策略,抑制阵风引起的无人机位姿剧烈扰动;最后,给出风扰场景下的着陆控制律及系统稳定性证明.基于孪生场景开展固定翼无人机多架次着陆飞行验证,通过与经典控制方案对比,验证了本文所提控制方法的有效性.In this paper,a twin-scenario driven autonomous landing flight control optimization scheme is proposed to solve practical problems such as the difficulty in modeling low-attitude airflow disturbance during fixed-wing unmanned aerial vehicle(UAV)landing.Firstly,a high-fidelity scenario simulation system was constructed by introducing twin technology,based on which landing flight data under various wind disturbance conditions were collected.Then a trajectory tracking learning control algorithm is designed to resist the influence of low-level wind disturbance by mining the historical safe landing flight experience.The online adjustment strategy of the desired landing trajectory is designed to resist the violent disturbance of the position and attitude of the UAVs caused by wind gusts.Finally,the landing control law and system stability are given under wind disturbance.Multiple sorts landing flights of fixed wing UAVs were verified in the twin scenario.The effectiveness of the proposed control method is verified by comparing with the classical control scheme.

关 键 词：固定翼无人机 自主着陆 低空风扰 学习控制 轨迹跟踪 

分 类 号：V279[航空宇航科学与技术—飞行器设计] V249.1