摘要
将飞机分解成若干面并分别建立当地气动力及力矩模型,应用大幅滚转振荡试验数据,最终建立了一种能够描述飞机横向非定常气动力特性的状态空间模型。采用粒子群全局优化算法对模型进行参数辨识,辨识结果和预测值符合试验数据,表明应用升力面分解思想建立横向状态空间模型是可行的。
Based on the large amplitude experimental data of one degree-of-freedom roll oscillations, a state-space model was developed to describe the lateral-directional unsteady aerodynamic characteristics by separating the aircraft into panels and modeling the local forces and moments. For this model, the global particle swarm optimization was used in parameter estimation program. There was agreement between mathematically predicted data and measured data. It is shown that the idea of developing lateral-directional state-space representation through splitting the aircraft into several lifting surfaces is feasible.
出处
《飞行力学》
CSCD
北大核心
2014年第5期464-467,476,共5页
Flight Dynamics
基金
航空科学基金资助(20133252046)
关键词
滚转振荡
非定常
状态空间模型
参数辨识
roll oscillations
unsteady
state-space model
parameter identification