四旋翼无人机飞行控制及路径规划算法研究

发布时间：2018-10-26 11:53

【摘要】：如今是无人机飞速发展的年代,无论是军用还是民用,无人机越来越体现出其巨大的实用价值,随着应用领域越来越广泛,人们对无人机的要求也越来越高,从基本的飞行控制到智能自主飞行,无人机的研究在向着更高水平发展。无人机的稳定控制是其进行一切任务的基础,论文依据仿人智能控制理论,设计了一种四旋翼无人机仿人智能控制器,通过分段操作实现对无人机的精确控制,为验证控制器的可行性和优越性,论文对其和传统的串级PID控制器进行了仿真对比,实验结果证明论文设计的控制器对四旋翼无人机的控制效果更优。无人机路径规划是无人机实现自主飞行的一个重要部分,而且由于无人机任务的复杂度不断增加,高效的飞行是必不可少的,所以无人机的路径规划技术受到更多关注。无人机路径规划是指在已知或未知环境条件下,指定无人机飞行的起点和终点,无人机自主完成飞行路径的设计工作,并且保证某项飞行指标最优。在移动机器入领域或者二维环境下,路径规划技术的发展相对成熟,已经有很多算法得到应用,像蚁群算法、遗传算法等,都取得了不错的效果,无人机路径规划在三维环境下进行,其复杂度有了很大升高,而且还要考虑无人机自身条件的约束等因素,使得问题更加复杂,很多算法都不能满足规划要求,需要进一步研究。论文在现有研究的基础上,先对较为常用的遗传算法进行了研究,对其进行改进从而用于路径规划中,取得了一定效果,但论文只研究了其在栅格建模的基础上的应用,考虑到无人机飞行环境的宽度和广度以及飞行路径的平滑度等因素,论文结合已有研究成果,进一步提出一种基于A*算法的Dubins路径规划算法,将无人机自身的转弯半径约束考虑在内,可以规划出一条平滑的最短飞行路径。文中对提出的规划算法进行了详细介绍,从原理到具体过程,从二维到三维,最后通过MATLAB仿真对该方法进行了仿真实验,验证了其有效性。
[Abstract]:Today is the era of rapid development of UAV, whether military or civilian, UAV more and more reflect its great practical value, with the application of more and more extensive, people's requirements for UAVs are also increasing. From basic flight control to intelligent autonomous flight, the research of UAV is developing to a higher level. The stability control of UAV is the basis of all its tasks. According to the theory of humanoid intelligent control, this paper designs a kind of humanoid intelligent controller of four-rotor UAV, and realizes the precise control of UAV by subsection operation. In order to verify the feasibility and superiority of the controller, the paper compares the controller with the traditional cascade PID controller. The experimental results show that the controller designed in this paper has better control effect on the four-rotor UAV. UAV path planning is an important part of UAV autonomous flight, and because of the increasing complexity of UAV mission, efficient flight is essential, so UAV path planning technology has received more attention. UAV path planning is to specify the starting point and end point of UAV flight under the condition of known or unknown environment. UAV independently completes the design of flight path and ensures the optimal flight index. In the mobile machine field or two-dimensional environment, the development of path planning technology is relatively mature, there have been a lot of algorithms have been applied, such as ant colony algorithm, genetic algorithm, and so on, have achieved good results. UAV path planning is carried out in three dimensional environment, its complexity has been greatly increased, and the constraints of UAV's own conditions must be taken into account, which makes the problem more complex, and many algorithms can not meet the planning requirements. Further study is needed. On the basis of the existing research, this paper first studies the more commonly used genetic algorithm, and improves it to get some effect in path planning, but the paper only studies its application on the basis of grid modeling. Considering the width and breadth of the UAV flight environment and the smoothness of the flight path, this paper proposes a Dubins path planning algorithm based on the A* algorithm combined with the existing research results. Taking the turning radius constraints of UAV into account, a smooth shortest flight path can be planned. In this paper, the proposed programming algorithm is introduced in detail, from the principle to the concrete process, from two to three dimensions. Finally, the simulation experiment of the method is carried out through MATLAB simulation, and the validity of the method is verified.
【学位授予单位】：青岛理工大学
【学位级别】：硕士
【学位授予年份】：2016
【分类号】：V279;V249

【相似文献】