摘要
采用一种适用于噪声环境的广义整体最小二乘算法,准确地辨识飞机的颤振模态参数.该算法结合有理传递函数模型,将带噪系统的辨识问题转化为广义整体最小二乘问题.利用线性的广义奇异值分解求解模型系数,避免了非线性优化的复杂计算.通过迭代法更新加权项,获得了接近于极大似然估计的辨识效果.最后利用试飞试验数据辨识飞机的模态参数,验证了该方法的有效性.
A generalized total least square algorithm in frequency domain is adopted for aircraft flutter modal parameter identification under noisy environment. Combing with a rational transfer function model, the identification of black box system with noisy data is transformed into of a generalized total least square problem, and the solution is solved by generalized singular value decomposition to avoid the complex nonlinear optimization. A nearly maximum likelihood properties can be achieved by updating weighted iterative generalized total least squares. The simulation with real flight test data shows the efficiency of the algorithm.
出处
《控制与决策》
EI
CSCD
北大核心
2006年第7期726-729,共4页
Control and Decision
基金
国家自然科学基金项目(69925306)
航空科技基金项目(01D53010)
关键词
参数辨识
广义整体最小二乘
试飞试验
Parameter identification
Generalized total least squares
Flight test
