四旋翼无人机的位置和姿态控制算法研究  

Position and Attitude Control Algorithm Study of Quadrotor UAV

作　　者：刘子龙[1] 窦鹏程 LIU Zi-long;DOU Peng-cheng(School of Optical-Electrical and Computer Engineering,University of Shanghai for Science and Technology,Shanghai 200093,China)

机构地区：[1]上海理工大学光电信息与计算机工程学院,上海200093

出　　处：《小型微型计算机系统》2022年第4期754-758,共5页Journal of Chinese Computer Systems

基　　金：国家自然科学基金项目(61074087)资助。

摘　　要：四旋翼无人机是一种非线性、强耦合、欠驱动系统.针对四旋翼存在参数不确定性和外部干扰等问题,本文提出了一种基于反步积分-迭代学习控制和自抗扰控制的位置-姿态控制算法.对于双闭环控制系统,内环采用自抗扰控制,通过扩张状态观测器可以实时观测和补偿内部耦合等建模时参数不确定性项和外部随机干扰.外环采用反步积分-迭代学习控制,因为反步法可以很好的进行轨迹跟踪但特别依赖模型的精确度且缺乏抗干扰能力,与迭代学习控制有机结合后,使得系统在有限时间内跟踪性能得到提高.仿真试验实现了四旋翼位置和姿态的跟踪控制,验证了所提控制算法的有效性.Quadrotor UAV is a nonlinear,strongly coupled,under-actuated system.In this paper,a position-attitude control algorithm based on backstepping integral-iterative learning control and active disturbance rejection control is proposed to solve the problem of parameter uncertainty and external disturbance of quadrotors.For the double closed loop control system,the inner loop adopts the active disturbance rejection control,and the extended state observer can observe and compensate the parameter uncertainties and external random disturbances such as the internal coupling in real time.The backstepping integral-iterative learning control is adopted for the outer loop,because the backstepping method can track the trajectory very well but it particularly depends on the accuracy of the model and lacks the ability of disturbance rejection.When combined with the iterative learning control,the tracking performance can be improved in limited time.The simulation experiment realizes the tracking control of the position and attitude of the quadrotor and verifies the effectiveness of the proposed control system.

关 键 词：四旋翼 反步积分 迭代学习 自抗扰 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]