改进的频域辨识方法及其在直升机建模中的应用

Modified frequency identification method and its application to helicopter modeling

中文关键词  直升机  状态空间模型  K平均聚类算法  频域辨识  复合窗函数法  模型简化

英文关键词  helicopter  state-space model  K-means clustering algorithm  frequency identification  composite windows  model simplifying

中文摘要

      本文提出了一种改进的直升机状态空间模型的频域系统辨识方法. 该方法根据飞行扫频数据, 得到包含直升机动力学模型耦合特性的非参数频率响应. 将模式识别中的K平均理论应用到搜索状态空间模型代价函数的最小值中, 根据机理建模结果拟合频率响应得到线性的六自由度直升机状态空间模型中的待辨参数. 频率响应的计算中应用了一种复合窗函数方法, 该方法综合不同窗口长度的频率响应得到一组优化的结果, 显著增加了动力学模型频带和频率响应的精度. 比较辨识得到的模型和飞行试验数据响应结果表明, 辨识得到的模型较好地反映了该型无人直升机在悬停状态下的动力学特性.

英文摘要

      A frequency identification method for a six-DoF state-space model of helicopter is presented. The overall concept is to extract a complete set of non-parametric input-to-output frequency responses that fully characterizes the coupled helicopter dynamics. This set of frequency responses is the basis for the model simplification, and for conducting a nonlinear search based on K-means clustering algorithm for a six-DoF linear state-space model that matches the frequency-response data set. A new method for combining the results of multi-input frequency-response analyses obtained from a range of spectral windows into a single optimized response is presented. This method significantly improves the dynamic range and the accuracy of the identified frequency-response relative to single-window methods. The accuracy of the identified model is validated by comparing the model-predicted responses with the responses collected during flight experiments.