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基于自抗扰控制的无人机抗风干扰自动起飞与着陆研究
其他题名Automatic Takeoff and Landing of UAV in Wind Disturbances Based on Active Disturbance Rejection Control
熊华
学位类型工学博士
导师易建强 ; 景奉水
2011-06-01
学位授予单位中国科学院研究生院
学位授予地点中国科学院自动化研究所
学位专业控制理论与控制工程
关键词无人机 起飞 着陆 风干扰 自抗扰控制 Unmanned Aerial Vehicle Uav Takeoff Landing Wind Disturbance Active Disturbance Rejection Control Adrc
摘要无人机(UAV)是无人驾驶飞机(Unmanned Aerial Vehicle)的简称,它是一种由动力驱动,可重复使用的航空器。由于在民用和军事领域的应用前景,无人机逐渐成为一个研究热点。 轮式起降飞机的飞行过程可以分为三个阶段:起飞阶段、空中飞行阶段和着陆阶段。虽然起飞及着陆阶段所占用的时间远小于空中飞行阶段,但是飞机的起飞和着陆往往是最容易出事故的环节。在起飞及着陆阶段,各种风干扰(风紊流、风切变、下垂阵风和侧风)将严重威胁飞机安全,因此,作为飞机的一种,无人机在各种风干扰下的起飞及着陆控制是一个难题。 自抗扰控制技术不需要直接测量扰动作用,也不需要事先知道扰动作用规律而能直接且实时地估计并补偿掉无人机的内扰和外扰(即风干扰),因此,自抗扰控制技术可用于设计无人机抗风自动起飞及抗风自动着陆控制系统。 以大翼展无人机的自动起飞及自动着陆控制研究为背景,对利用自抗扰控制技术控制大翼展无人机在各种风干扰下实现自动起飞及自动着陆进行了深入研究,主要完成了以下工作: (1)建立了无人机三轮滑跑、两轮滑跑和空中飞行三个阶段的数学模型。创新点为在三轮滑跑和两轮滑跑数学模型的基础上分别推导出三轮滑跑和两轮滑跑阶段地面对无人机各机轮的支撑力公式,得出了地面对两后轮的支撑力为互补关系的结论。另外,利用支撑力的变化作为无人机起飞时三轮滑跑、两轮滑跑和空中飞行三个阶段的切换依据,得出无人机起飞模型。 (2)对无人机的数学模型进行演变,证明无人机油门-速度通道的阶次(即通道输出与输入的传递函数的阶次)为1,升降舵-俯仰角通道、副翼-滚转角通道和方向舵-偏航角通道的阶次均为2。接着,为相应的油门-速度通道设计了1阶自抗扰控制器,为相应的升降舵-俯仰角通道、副翼-滚转角通道和方向舵-偏航角通道分别设计了2阶自抗扰控制器。 (3)为大翼展无人机提出基于自抗扰控制的无人机抗风自动起飞控制方案,设计无人机抗风自动起飞纵向控制系统和无人机抗风自动起飞横向控制系统,使无人机在遭遇较大幅度风干扰(下垂阵风、风紊流和侧风)时能够安全起飞。 (4)为大翼展无人机提出基于自抗扰控制的无人机抗风自动着陆控制方案,设计无人机抗风自动着陆纵向控制系统和无人机抗风自动着陆横向控制系统,使无人机在遭遇较大幅度风干扰(风紊流、风切变和侧风)时能够安全着陆。 总的来说,本文对利用自抗扰控制技术控制大翼展无人机在各种风干扰下实现自动起飞及自动着陆进行了深入研究,为后续无人机自动起飞及自动着陆控制系统的实际应用提供了必要的理论依据和研究经验。随着相关技术的发展和完善,将基于自抗扰控制技术的无人机自动起飞及自动着陆控制系统转化为实际机载飞控系统,将对我国无人机的发展具有积极意义。
其他摘要Unmanned Aerial Vehicle, which is simplified as UAV, is an unmanned and reusable aircraft. It has attracted considerable attention due to their promising benefits in civil and martial applications. A flight of an aircraft which taxies on wheels can be separated into three phases: takeoff phase, flying in the air phase, and landing phase. Although the time spent at the takeoff and landing is much less than the time spent at the flying in the air phase, the takeoff and landing are the most dangerous phases which most accidents occur at. During the takeoff and landing phases, wind disturbances (turbulence, wind shear, gust, and crosswind) will threaten the aircraft severely, therefore, it is a significant problem to control the UAV to takeoff and land safely under various wind disturbances. The Active Disturbance Rejection Control (ADRC) technique has the unique characteristic of directly and real-timely estimating the UAV’s internal and external disturbances (i.e. wind disturbances) without measuring the disturbances or knowing the rules of the disturbances. Therefore, ADRC is involved to design the automatic takeoff control system and the automatic landing control system for the UAV. In this dissertation, the automatic takeoff control and the automatic landing control of certain UAV with wide span under various wind disturbances are deeply studied based on the ADRC technique. The main contributions of this dissertation include the following issues: Firstly, the three-wheel taxiing model, the two-wheel taxiing model, and the flying in the air model of the UAV are established. The formulas of supporting forces acting on the UAV’s nose wheel and main wheels by the ground are deduced from the three-wheel taxiing model and the two-wheel taxiing model. It can be concluded that the supporting forces of the main wheels are mutually complementary. In the UAV’s takeoff model, the supporting forces of the three wheels are used as indicators to switch the three-wheel taxiing phase, the two-wheel taxiing phase, and the flying in the air phase. Secondly, by reformulating the UAV’s model, we confirm that under some simplifications the throttle-velocity subsystem is of first-order, the elevator-pitch angle subsystem, the aileron-roll angle subsystem, and the rudder-yaw angle subsystem are of second-order respectively. Then, a first-order Active Disturbance Rejection Controller (ADRCer) is designed for the throttle-velocity subsystem. Besides...
馆藏号XWLW1661
其他标识符200818014628022
语种中文
文献类型学位论文
条目标识符http://ir.ia.ac.cn/handle/173211/6382
专题毕业生_博士学位论文
推荐引用方式
GB/T 7714
熊华. 基于自抗扰控制的无人机抗风干扰自动起飞与着陆研究[D]. 中国科学院自动化研究所. 中国科学院研究生院,2011.
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