计算机应用研究2011，Vol.28Issue(4)：1238-1241,4.DOI:10.3969/j.issn.1001-3695.2011.04.009
态空间系统的梯度优化辨识及收敛性分析
Gradient optimization identification for state-space systems and convergence analysis
摘要
Abstract
In order to solve the problem which was caused by the nonlinearity and nonconvexity between the output error and the system parameters in state-space model, proposed a gradient optimization identification for parameter estimation of state-space systems. Analyzed the principle of gradient identification based on local linearization. Moreover, determined the parameter search direction based on the QR and SVD methods. And gave the iterative identification algorithm for parameter estimation.Furthermore, analyzed the convergence of the identification algorithm and also gaven the analytic expression of the convergence rate of the identification algorithm. Finally, the effectiveness of the proposed method is illustrated by numerical simulation.关键词
系统辨识/状态空间系统/梯度优化/收敛性分析Key words
system identification/ state-space systems/ gradient optimization/ convergence analysis分类
信息技术与安全科学引用本文复制引用
衷路生,樊晓平,杨辉,瞿志华,齐叶鹏,颜争..态空间系统的梯度优化辨识及收敛性分析[J].计算机应用研究,2011,28(4):1238-1241,4.基金项目
国家自然科学基金资助项目(60870010,60864004,60904049) （60870010,60864004,60904049）
国家"863"计划资助项目(2008AA04Z129) （2008AA04Z129）
