A practical filter error method for aerodynamic parameter estimation of aircraft in turbulence

作     者：Qing WANG Fengqi ZHENG Weiqi QIAN Di DING Qing WANG;Fengqi ZHENG;Weiqi QIAN;Di DING

作者机构：State Key Laboratory of AerodynamicsChina Aerodynamics Research and Development CenterMianyang 621000China Computational Aerodynamics InstituteChina Aerodynamics Research and Development CenterMianyang 62100China 

出 版 物：《Chinese Journal of Aeronautics》 (中国航空学报（英文版）)

年 卷 期：2023年第36卷第2期

页      面：17-28页

核心收录：

学科分类：0711[理学-系统科学] 08[工学] 080103[工学-流体力学] 0714[理学-统计学（可授理学、经济学学位）] 0811[工学-控制科学与工程] 0801[工学-力学（可授工学、理学学位）] 

基　　金：supported by the National Natural Science Foundation of China(No.11802325)。 

主　　题：Aircraft aerodynamics Atmosphere turbulence Flight tests Kalman filter Maximum likelihood estimation Measurement noise Parameter estimation Stability and control derivatives 

摘      要：It is common for aircraft to encounter atmospheric turbulence in flight tests.Turbulence is usually modeled as stochastic process noise in the flight dynamics equations.In this paper,parameter estimation of nonlinear dynamic system with both process and measurement noise was studied,and a practical filter error method was proposed.The linearized Kalman filter of first-order approximation was used for state estimation,in which the filter gain,along with the system parameters and the initial states,constituted the parameter vector to be estimated.The unknown parameters and measurement noise covariance were estimated alternately by a relaxation iteration method,and the sensitivities of observations to unknown parameters were calculated by finite difference approximation.Some practical aspects of the method application were discussed.The proposed filter error method was validated by the flight simulation data of a research aircraft.Then,the method was applied to the flight tests of a subscale aircraft,and the aerodynamic stability and control derivatives were estimated.All the estimation results were compared with the results of the output error method to demonstrate the effectiveness of the approach.It is shown that the filter error method is superior to the output error method for flight tests in atmospheric turbulence.