Filtering based Recursive Least Squares Identification for Non-uniformly Sampled Systems

摘要：

In this paper, a filtering based recursive least squares algorithm is derived for identification of the nonuniformly sampled Box-Jenkins systems. The basic idea is to use an estimated noise transfer function to filter the input-ouput data, to obtain two identification models containing the parameters of the system model and the noise model respectively, and to present the filtering based recursive least squares method to identify the parameters of these two models, by replacing the unmeasurable terms in the information vectors with their estimates. Finally, an illustrative example is given to indicate that the proposed algorithm can generate more accurate parameter estimation compared with the auxiliary model based recursive generalized extended least squares algorithm.

关键词： Non-uniform Sampling Multirate Systems Least Squares Filtering Parameter Estimation

作者: Li Xie Huizhong Yang Feng Ding

作者单位: School of Communication and Control Engineering, Jiangnan University, Wuxi, 214122

会议类型: 国际会议

会议名称: The 22nd China Control and Decision Conference(2010年中国控制与决策会议)

会议地点: 徐州

会议语种:英文

页码: 1123-1128

在线出版日期: 2010-05-26（万方平台首次上网日期，不代表论文的发表时间）