Recursive Subspace Model Identification Based on Orthogonal Projection and Principal Component Analysis

摘要：

Most subspace identification methods are developed for linear time-invariant system. However, in reality, most systems are time-varying. Hence the recursive version of subspace identification methods is urgently desired. In this paper, we propose a unifying framework of recursive subspace model identification algorithm, which is based on the orthogonal projection and principal component analysis (PCA). Based on our framework, the bona fide recursive algorithm is applied to update the QR factorization. Two recursive subspace model identification algorithms are developed for open loop and closed loop condition, respectively. The numerical simulations demonstrate the efficiency of the two algorithms comparing with other algorithms.

关键词： system identification subspace methods recursive algorithm

作者: Guozheng Tao

作者单位: epartment of Electrical Engineering Changzhou Institute of Mechatronic Technology Changzhou 213164, Jiangsu, P.R.China

会议类型: 国际会议

会议名称: The 2010 International Conference on Computer Application and System Modeling(2010计算机应用与系统建模国际会议 ICCASM 2010)

会议地点: 太原

会议语种:英文

页码: 422-429

在线出版日期: 2010-10-22（万方平台首次上网日期，不代表论文的发表时间）