【作者】 尹彦清；

【导师】 徐锦法；

【作者基本信息】 南京航空航天大学 ， 飞行器设计， 2011， 硕士

【摘要】 无人机在现代战场中发挥着越来越大的作用。由于其具有机动性高、零伤亡和低成本等独特的优点,世界各国对无人机的发展给予了极大的关注。随着无人机在军民用领域应用的日益广泛,人们对无人机飞行性能的要求越来越高,赋予无人机智能以实现其自主飞行的呼声越来越大。现代计算机信息技术、人工智能和自主控制技术的发展,指出了无人机自主飞行控制发展的方向。本文研究的主要内容是根据无人机自主飞行的控制要求,设计基于神经网络补偿的无人机动态逆自主飞行控制系统。首先介绍了无人机的发展历史和国内外发展现状,分析了未来无人机面向自主控制的发展趋势。其次总结了传统控制方法在无人机自主飞行控制研究中的不足,介绍了现代先进的飞行控制律设计方法。然后运用人工神经网络和逆系统控制方法,从内外回路两个方面,提出了样例无人直升机自主飞行控制系统基本结构。基于该结构,根据动态逆反馈线性化理论设计无人机内回路姿态控制系统和外回路轨迹控制系统,并分析模型跟踪误差动力特性,再根据误差特性设计神经网络误差补偿器,给出神经网络在线学习调整算法。最后运用VS程序设计工具开发了无人机自主飞行控制仿真软件,对控制系统理论的正确性和合理性进行仿真实验验证,并参照飞行品质规范进行了典型任务科目的飞行仿真实验。仿真结果表明本文设计的控制系统具有较高的控制精度和自主适应性,符合自主飞行控制要求。更多还原

【Abstract】 Nowadays, the UAV plays a more and more important role in modern wars. Because of its high maneuverability, zero death and low cost, countries all around the world put much effort into studying it. As the application of UAV in the civil fields is becoming more and more broad, people pays more attention to its flight performance. So it is urgent to achieve the autonomous flight. The development of the computer and information technology, artificial intelligence and autonomous control technology promote the further studying on the UAV’s autonomous flight control system.The main content of this paper is to design the UAV’s autonomous flight control system, according to the UAV’s control requirements. First, the history and development of the UAV is introduced, and the development tendency of the UAV’s autonomous flight control system is analyzed as well. Then, the traditional control methods are described. Based on their disadvantages in the studying of the UAV’s autonomous flight control system, the advanced control methods are proposed, such as the dynamical inversion flight control method. Using this method, the basic structure of the UAV’s autonomous flight control system is conducted, from the respects of the inner-loop and the outer-loop. According to this structure, the inner-loop attitude control system and the trajectory control system are designed respectively. Error compensation system based on Neural Network is developed according to the characteristics of model tracking error. Besides, online learning algorithm of the Neural Network is given. Finally, implementing the VS programming language, the UAV’s autonomous flight control and simulation software is developed. Within the simulation environment, the correctness and rationality is validated, and the simulation experiment of typical flight task is performed reference to the flight quality standard. The simulation result shows that the control system designed in the paper has high control accuracy as well as adaptability,and can meet the requirements of the autonomous flight well.更多还原