On extended state Kalman filter-based identification algorithm for aerodynamic parameters
Wenyan Bai1
Ruizhe Jia2
Peng Yu2
Wenchao Xue3
1.Beijing Aerospace Automatic Control Institute,Beijing 100854,China2.School of Automation and Electrical Engineering,University of Science and Technology Beijing,Beijing 100083,China;Key Laboratory of Knowledge Automation for Industrial Processes,Ministry of Education,Beijing 100083,China3.Key Laboratory of Systems and Control,Institute of Systems Science,Academy of Mathematics and Systems Science,Chinese Academy of Sciences,Beijing 100190,China
摘要：In this paper,the problem of time-varying aerodynamic parameters identification under measurement noises is studied.By analyzing the key aerodynamic parameters that affect the aircraft control system,a system model with extended states for identifying equivalent aerodynamic parameters is established,and error parameters are extended to the system state,avoiding the difficulty caused by the unknown dynamic in the system.Furthermore,an identification algorithm based on extended state Kalman filter is designed,and it is proved that the algorithm has quasi-consistency,thus,the estimation error can be evaluated in real time.Finally,the simulation results under typical flight scenarios show that the designed algorithm can accurately identify aerodynamic parameters,and has desired convergence speed and convergence precision.
机标关键词：identificationalgorithmkalmanstateaerodynamicextendedfilter-basedparameters
论文发表日期：2024-05-05
在线出版日期：2025-08-15（本平台首次上网日期，不代表文献的发表时间）
页数：9( 235-243 )
英文信息