Bias Compensation based Recursive Least Squares Identification for Equation Error Models with Colored Noises

摘要：

　　It is well known that the least squares estimation of ARMAX models is biased.In this paper,by combining the principle of bias compensation and hierarchical identification,a new identification is established for this equation error model with moving average noises.The proposed estimate of the system parameter is given by the least squares estimate modified by a correction term.A numerical example is employed to show the advantage of the proposed estimation algorithm.

关键词： Bias compensation Least squares estimation Covariance

作者: WU Ai-Guo YANG Fan QIAN Yang-Yang

作者单位: Shenzhen Graduate School,Harbin Institute of Technology,Shenzhen 518055,P.R.China;Center for Control Shenzhen Graduate School,Harbin Institute of Technology,Shenzhen 518055,P.R.China

会议类型: 国际会议

会议名称: The 33th Chinese Control Conference第33届中国控制会议

会议地点: 南京

会议语种:英文

页码: 6715-6720

在线出版日期: 2014-07-28（万方平台首次上网日期，不代表论文的发表时间）