%0 Journal Article
%T Gradient optimization identification for state-space systems and convergence analysis<br>态空间系统的梯度优化辨识及收敛性分析*
%A ZHONG Lu-sheng
%A FAN Xiao-ping
%A YANG Hui
%A QU Zhi-hu
%A QI Ye-peng
%A YAN Zheng
%A <br>衷路生
%A 樊晓平
%A 杨辉
%A 瞿志华
%A 齐叶鹏
%A 颜争
%J 计算机应用研究
%D 2011
%I 
%X In order to solve the problem which is caused by the nonlinearity and nonconvexity between the output error and the system parameters in state-space model, gradient optimization identification is proposed for parameter estimation of state-space systems. The principle of gradient identification based-on local linearization is analyzed. Moreover, the parameter search direction is determined based on the QR and SVD methods. And iterative identification algorithm is given for parameter estimation. Furthermore, the convergence of the identification algorithm is analyzed and the analytic expression of the convergence rate of the identification algorithm is also given. Finally, the effectiveness of the proposed method is illustrated by numerical simulation.
%K system identification
%K state-space systems
%K gradient optimization
%K convergence analysis<br>系统辨识
%K 状态空间系统
%K 梯度优化
%K 收敛性分析
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=A9D9BE08CDC44144BE8B5685705D3AED&aid=5405B20936821579F626D7A4A21F43BF&yid=9377ED8094509821&vid=D3E34374A0D77D7F&iid=E158A972A605785F&sid=5C10CB62DEB8898B&eid=A3FC76ED9EF62E85&journal_id=1001-3695&journal_name=计算机应用研究&referenced_num=0&reference_num=5