Comparison of linear and nonlinear aerodynamic parameter estimation approaches for an unmanned aerial vehicle using unscented Kalman filter

作     者：李蒙 刘莉 S.M.VERES 

作者机构：School of Aerospace EngineeringBeijing Institute of Technology School of Engineering SciencesUniversity of Southampton 

出 版 物：《Journal of Beijing Institute of Technology》 (北京理工大学学报（英文版）)

年 卷 期：2011年第20卷第3期

页      面：339-344页

核心收录：

学科分类：0810[工学-信息与通信工程] 08[工学] 0805[工学-材料科学与工程（可授工学、理学学位）] 082503[工学-航空宇航制造工程] 0825[工学-航空宇航科学与技术] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：Supported by the Engineering and Physical Sciences Research Council(EPSRC) UK(EP/F037570/1) 

主　　题：unmanned aerial vehicle aerodynamic parameter estimation unscented Kalman filter 

摘      要：Aerodynamic parameter estimation provides an effective way for aerospace system modeling using measured data from flight tests, especially for the purpose of developing elaborate simulation environments and designing control systems of unmanned aerial vehicle （UAV） with short design cycles and reduced cost. However, parameter identification of airplane dynamics by nonlinear mod- els is complicated because of the noisy and biased sensor measurements. Using linear models for system identification is an alternative way if the fidelity can be guaranteed, as control design procedures are better established in linear systems. This paper considers the application and comparison of linear as well as nonlinear aerodynamic parameter estimation approaches of an UAV using unscented Kalman filter （UKF）. It also highlights the degree of deterioration of the linear model in the UKF identification process. The results show that both the linear and nonlinear methodologies can accurately estimate the control system design. Furthermore, considering loss of accuracy to be negligible, the linear model can be employed for control design of the UAV as presented here.