Adaptive control of unmanned aerial vehicles: Theory and flight tests
Adaptive control of unmanned aerial vehicles: Theory and flight tests
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DOI：
10.1007/978-90-481-9707-1_61
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发表时间：
2015
期刊：
影响因子：
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通讯作者：
S. Kannan;Girish V. Chowdhary;Eric N. Johnson
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文献类型：
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作者：
S. Kannan;Girish V. Chowdhary;Eric N. Johnson
通常，无人驾驶飞行器是欠驱动系统，也就是说，它们具有比自由度更少的独立控制输入。例如，在直升机中，身体轴滚转、俯仰、偏航和高度被完全驱动。然而，横向和纵向平移运动只能通过倾斜推力矢量来实现。本章提出了一个六自由度的飞行控制算法，可以跟踪位置和姿态轨迹。近似逆模型的车辆姿态和位置动力学的反馈线性化，导致一个内环，跟踪姿态和角速度和外环，跟踪位置和速度命令。单个自适应元件用于补偿两个环路中的反演误差（不确定性）。在真实的飞机上实现自适应控制设计的一个关键挑战是处理执行器幅值和速率饱和。这样的饱和元件不能容易地在逆模型中捕获，并且导致在饱和期间自适应元件中的不正确学习。提供了一种精确地去除这种不正确学习的机制。此外，还引入非线性参考模型来减轻闭环系统进入飞行包线区域导致失控的风险。所得到的自适应控制器接受包括期望的位置、速度、姿态和角速度的轨迹命令，并产生飞行控制所需的归一化致动器信号。还提供了对基线自适应控制系统的修改，其使得能够长期保持自适应元件内的不确定性近似。该体系结构通过几种固定翼和旋翼无人机的飞行试验得到验证，包括一种145磅重的直升机无人机（雅马哈RMAX或GTMax）、一种比例模型固定翼飞机（GTEdge）和一种小型涵道风扇（GTSpy）。
Typically, unmanned aerial vehicles are underactuated systems, that is, they have fewer independent control inputs than degrees of freedom. In a helicopter, for example, the body axes roll, pitch, yaw, and altitude are fully actuated. However, lateral and longitudinal translational motion is only possible by tilting the thrust vector. This chapter develops a six degree-of-freedom flight control algorithm that can track both position and attitude trajectories. Approximate inverse models for vehicle attitude and position dynamics are used for feedback linearization leading to an inner-loop that tracks attitude and angular rate and an outer-loop that tracks position and velocity commands. A single adaptive element is used to compensate for inversion errors (uncertainty) in both loops. A key challenge in realizing an adaptive control design on real aircraft is dealing with actuator magnitude and rate saturation. Such saturation elements cannot be easily captured in inverse models and leads to incorrect learning in the adaptive element during periods of saturation. A mechanism to exactly remove such incorrect learning is provided. Additionally, nonlinear reference models are introduced to mitigate the risks of the closed-loop system entering regions of the flight envelope that result in loss-of-controllability. The resulting adaptive controller accepts trajectory commands comprising of desired position, velocity, attitude, and angular velocity and produces normalized actuator signals required for flight control. A modification to the baseline adaptive control system is also provided that enables long-term retention of the uncertainty approximation within the adaptive element. This architecture is validated through flight tests on several fixed wing and rotorcraft UAVs, including a 145-lb helicopter UAV (Yamaha RMAX or GTMax), a scale model fixed-wing aircraft (GTEdge), and a small ducted fan (GTSpy).