基于UKF的四旋翼飞行器空气阻力系数辨识  

Identification of air resistance coefficient of quad-rotor aircraft based on UKF

作　　者：牛其磊 张卫东[1,2,3] NIU Qilei;ZHANG Weidong(Department of Automation,Shanghai Jiao Tong University,Shanghai 200240,China;Key Laboratory of System Control and Information Processing,Ministry of Education,Shanghai 200240,China;Shanghai Engineering Research Center of Intelligent Control and Management,Shanghai 200240,China)

机构地区：[1]上海交通大学自动化系,上海200240 [2]系统控制与信息处理教育部重点实验室,上海200240 [3]上海工业智能管控工程技术研究中心,上海200240

出　　处：《传感器与微系统》2023年第4期131-134,共4页Transducer and Microsystem Technologies

基　　金：国家自然科学基金资助项目(61473183,61627810)。

摘　　要：针对微小型四旋翼飞行器动力学模型存在强非线性和强耦合性,空气阻力系数难以通过实验获得的问题,设计了一种机理建模与辨识建模相结合的方法,将待辨识参数作为状态变量增广到飞行器的动力学模型中,然后采用无迹卡尔曼滤波(UKF)算法对状态量进行估计。针对UKF算法发散的问题采用了一种基于状态方差阵对角相似分解的采样策略,最终有效辨识出了飞行器的三轴空气阻力系数。实验结果表明了UKF应用于四旋翼飞行器模型参数辨识的可行性与有效性。Due to the strong nonlinearity and strong coupling problems,the coefficient of air resistance in the dynamics model of the miniature quad-rotor aircraft is difficult to obtain experimentally.A combined mechanism modeling and identification modeling method is proposed.The parameters to be identified are extended to the aircraft dynamics model as state variables,and then the unscented Kalman filtering(UKF)algorithm is used to estimate the state quantities.A sampling strategy based on the diagonal similarity decomposition of state variance matrix is used to solve the divergence problem of UKF algorithm.Finally,the three-axis air resistance coefficients of the aircraft is effectively obtained.Experimental results show that it is feasible and effective to use UKF for model parameter identification of quad-rotor aircraft.

关 键 词：无迹卡尔曼滤波 四旋翼飞行器 模型辨识 参数估计 空气阻力系数 

分 类 号：TP391[自动化与计算机技术—计算机应用技术] V212.4[自动化与计算机技术—计算机科学与技术]