四旋翼无人飞行器飞行控制方法研究

发布时间：2018-01-03 16:11

本文关键词：四旋翼无人飞行器飞行控制方法研究　出处：《中国计量学院》2015年硕士论文　论文类型：学位论文

【摘要】：近年来,四旋翼无人飞行器应用领域得到快速扩展,尤其军用和民用方面,被用于执行各种任务,而且,其商业化趋势也正在凸显。本课题主要研究了四旋翼无人飞行器的飞行控制方法,针对现有四旋翼无人飞行器飞行控制存在的问题,提出了不同的控制方法。四旋翼无人飞行器动力学数学模型具有欠驱动、强耦合、非线性特点,导致控制器设计难度加大。为了更好地实现四旋翼无人飞行器位置与姿态跟踪控制,同时,缩短稳定时间以及获得确切的滑模切换面系数,本文将模型分解为全驱动和欠驱动两个子系统。主要研究内容如下:(1)采用一种新型鲁棒最终滑模控制设计全驱动子系统的控制器。该方法能够保证状态变量迅速收敛于它们的期望值,缩短稳定时间,从而该子系统的状态变量成为欠驱动子系统的时间常量,强耦合性问题得到改善;采用一种滑模控制设计欠驱动子系统的控制器,该方法能够保证状态变量在有限时间内收敛于它们的期望值,从而整体上实现四旋翼无人飞行器位置与姿态跟踪控制。此外,仿真实验验证了该控制方法的有效性和鲁棒性。(2)采用一种二阶滑模控制设计全驱动与欠驱动子系统的控制器。考虑到,滑模切换面的系数是非线性的,但现有的大多数研究工作者进行仿真实验时,该系数直接被赋予具体数值,本文运用霍尔维兹稳定条件,最终得到了确切的滑模切换面系数。接着,为了在控制输入饱和条件下对四旋翼无人飞行器进行有效地控制,本文采用了一种基于控制输入饱和的二阶滑模控制方法。此外,仿真实验也验证了该两种控制方法的有效性和鲁棒性。(3)采用最优卡尔曼滤波器算法对两个子系统进行状态估计。考虑到过程白噪声和测量白噪声存在的可能性,本文采用了外推法将动力学模型离散化和线性化处理后,利用最优卡尔曼滤波器来估计状态变量,仿真实验证明该算法削弱了过程白噪声和测量白噪声的干扰。
[Abstract]:In recent years, the applications of four-rotor unmanned aerial vehicles (UAVs) have been rapidly expanded, especially in military and civilian areas, used for various missions, and. The commercial trend is also prominent. This paper mainly studies the flight control methods of four-rotor unmanned aerial vehicle (UAV), aiming at the existing problems of four-rotor UAV flight control. Different control methods are proposed. The dynamic mathematical model of four-rotor unmanned aerial vehicle (UAV) has the characteristics of underactuation, strong coupling and nonlinearity. In order to achieve better position and attitude tracking control of four-rotor unmanned aerial vehicle (UAV), the stabilization time is shortened and the exact coefficient of sliding mode switching surface is obtained. In this paper, the model is decomposed into two subsystems: full drive subsystem and underdriven subsystem. The main research contents are as follows: 1). A new robust ultimate sliding mode control is used to design the controller of the full drive subsystem. This method can ensure that the state variables converge rapidly to their expected values. The stability time is shortened, so that the state variable of the subsystem becomes the time constant of the underdriven subsystem, and the strong coupling problem is improved. A sliding mode control is used to design the controller of underactuated subsystem. This method can ensure that the state variables converge to their expected values in a finite time. Thus, the position and attitude tracking control of the four-rotor unmanned aerial vehicle is realized as a whole. Simulation results verify the effectiveness and robustness of the proposed control method. A second-order sliding mode control is used to design the full drive and underactuated subsystem controllers. The coefficients of the sliding mode switching surface are considered to be nonlinear. However, when most researchers do simulation experiments, the coefficients are directly assigned to specific values. In this paper, the exact coefficient of sliding mode switching surface is obtained by using Holwitz stability condition. In order to control the four-rotor unmanned aerial vehicle effectively under the condition of control input saturation, a second-order sliding mode control method based on control input saturation is used in this paper. Simulation results also verify the effectiveness and robustness of the two control methods. The optimal Kalman filter algorithm is used to estimate the state of the two subsystems, considering the possibility of the existence of process white noise and measurement white noise. In this paper, the dynamic model is discretized and linearized by extrapolation method, and the optimal Kalman filter is used to estimate the state variables. The simulation results show that the algorithm reduces the process white noise and the measurement white noise interference.
【学位授予单位】：中国计量学院
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：V249.12

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