基于滑窗QR和快速PCA算法的自适应子空间辨识

被引:5
作者
李喆 [1 ,2 ]
谢磊 [1 ]
孙培 [1 ]
WANG Xun [3 ]
KRUGER Uwe [3 ]
机构
[1] 浙江大学智能系统与控制研究所工业控制技术国家重点实验室
[2] 扬州大学水利与能源动力工程学院
[3] 伦斯勒理工学院生物医学工程系
关键词
滑窗QR分解; 主元分析; 子空间辨识; 自适应辨识;
D O I
10.16183/j.cnki.jsjtu.2015.11.018
中图分类号
N945.14 [系统辨识];
学科分类号
摘要
基于滑窗QR分解不但能快速、准确地更新正交投影,同时还可提供其协方差的rank-k更新表达,提出了一个用于信号子空间更新的快速PCA算法.通过对进行主元分析(PCA)计算的非线性迭代部分最小二乘算法(Non-linear Iterative Partial Least Squares,NIPALS)计算过程的改进,将特征向量的更新转化为小维度辅助向量的更新,在满足特征值和特征向量更新精度的同时,有效地提高了计算速度.将滑窗QR和快速PCA算法用于子空间辨识算法的自适应更新,数值仿真验证了此自适应子空间辨识算法的有效性.
引用
收藏
页码:1690 / 1695+1700 +1700
页数:7
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