基于CIFER平台的旋翼无人机系统辨识

摘要在对旋翼无人机进行控制器设计时，通常需要建立能够描述其完整动态特性的物理模型。本文利用系统辨识方法为旋翼无人机建模。常用的辨识方法有时域和频域两种，相对于时域系统辨识而言，频域系统辨识有着计算速率快、噪声消除方便等优点，这一方法也在大量实验和实际应用中日趋完善。CIFER是一种利用扫频输入进行频域系统辨识的综合性软件包，包含了从数据处理到模型辨识的全部模块，可以快速、准确地得到数学模型。79707

本文对四旋翼无人机不同飞行模式下的系统辨识进行了研究。根据实验数据，通过频率响应辨识和多输入辨识，分别建立了四旋翼无人机正常飞行、侧飞飞行、转弯飞行和起降飞行四种模式下的单输入/多输入系统模型，并进行了仿真与实验验证。

毕业论文关键词四旋翼无人机频域辨识 CIFER 传递函数模型

Title The quadrotor unmanned aerial vehicle (UAV) system identification based on CIFER platform

Abstract With the controller design of quadrotor unmanned aerial vehicle (UAV), usually there is necessary to establish a physical model can describe the complete dynamic characteristics, firstly。 In this paper, the quadrotor model is set up by using the system identification method。 There are commonly time domain and frequency domain two methods for quadrotor modeling。 Comparing with the time domain identification method, the frequency domain identification have many advantages such as calculation quickness and noise elimination convenience。 The frequency domain method is also becoming more complete with a large number of experiments and practical applications。 CIFER is a kind of integrated software package for frequency domain system identification using frequency sweep input, including data processing, model identification and so on all modules which can obtain the model quickly and accurately。

In this paper, several flight modes are identified for quadrotor UAV。 According to the experimental data, the four patterns of single input/multi-input system model are established, including normal flight mode, roll flight mode, turn flight mode and landing flight mode, via using frequency response identification recognition, and multi-input identification。 It is finally simulated to verify the identification results and the effectiveness。

Keyword UAV frequency identification CIFER transfer function

1 绪论 1

1。1 旋翼无人机辨识的意义 1

1。2 旋翼无人机频域法系统辨识建模的发展及现状 2

1。3 本文结构 3

2 旋翼无人机系统辨识及 CIFER 介绍 4

2。1 旋翼无人机系统辨识 4

2。2 频域与时域辨识方法比较 4

2。3 CIFER 软件功能及原理介绍基于CIFER平台的旋翼无人机系统辨识:http://www.youerw.com/zidonghua/lunwen_92281.html