信息与控制2016，Vol.45Issue(3)：294-300,7.DOI:10.13976/j.cnki.xk.2016.0294
TISO-OEAR模型的分解递推最小二乘辨识方法
Decomposition-based Recursive Least Squares Algorithm for TISO-OEAR Model
摘要
Abstract
To address the problem of the large amount of computation required in the parameter estimation process of output error models,we propose a decomposition-based recursive least squares (DRLS) algorithm.The basic idea is to decompose a two-input single-output (TISO) system into three subsystems,and then identify each of the three subsystems.The DRLS algorithm is an effective method for solving large computing problems and the complex identification models of large-scale systems.We perform a simulation to verify the validity and superiority of the proposed algorithm,and summarize the characteristics of the proposed and conventional algorithms.关键词
分解技术/递推辨识/最小二乘/参数估计/两输入单输出Key words
decomposition technique/recursive identification/least squares/parameter estimation/two-input single-output分类
信息技术与安全科学引用本文复制引用
石文林,卢先领..TISO-OEAR模型的分解递推最小二乘辨识方法[J].信息与控制,2016,45(3):294-300,7.基金项目
国家自然科学基金资助项目(61174021) （61174021）
江苏省产学研联合创新资金前瞻性联合研究资助项目(BY2014023-31) （BY2014023-31）
江苏省“六大人才高峰”资助项目(WLW-007) （WLW-007）
