数字化试飞平台下基于PSO的某型初级教练机飞行品质参数辨识试飞工程方法研究  

Research on Flight Test Engineering Method for Identification of Flight Quality Parameters for Certain Type of Primary Trainer Based on PSO at Digital Flight Test Platform

作　　者：赵明明 韩默 陶翔 史阳 Zhao Mingming;Han Mo;Tao Xiang;Shi Yang(AVIC Hongdu,Nanchang,Jiangxi,330095)

机构地区：[1]航空工业洪都,江西南昌330095

出　　处：《教练机》2021年第3期63-68,共6页Trainer

摘　　要：飞机飞行品质系统辨识是根据飞机系统的输入和输出响应时间历程求取该系统的数学模型及模型中的各参数的过程。本文给出一种在飞行试验中辨识飞机飞行品质短周期模态特性参数辨识试飞工程方法,首先应用连续域等效低阶系统传递函数来描述飞行品质模态特性系统,然后采用基于粒子群算法(Particle Swarm Optimization,PSO)的离散递推最小二乘算法,建立待估参数准则函数,通过极小化待估参数准则函数,求得参数的估计值,最后对辨识的模型进行验证。仿真算例表明该方法具有良好的收敛性和跟随性。The identification of flight quality system for aircraft is a process to obtain the mathematical model of this system and each parameter of the model,according to the input and output response time course of the aircraft system.This paper provides a flight test engineering method for parameters identification of short period modal characteristics to identify the aircraft flight quality during a flight test.Firstly,use the continuous domains equivalent low order system transfer function to describe the flight quality modal characteristics system;secondly,adopt the discrete recursive minimum multiplication algorithm based on PSO(particle swarm optimization)to establish the estimating parameter criterion function,and the estimated value of parameter could be obtained by minimizing the estimating parameter criterion function;finally,carry out the verification for the identified model.The simulation example shows that this method has good astringency and following performance.

关 键 词：飞行品质 等效低阶系统 短周期 粒子群算法 参数辨识 

分 类 号：V271.6[航空宇航科学与技术—飞行器设计]