东篱科研大数据发现系统（DRDS）

位置：成果数据库 > 期刊 > 期刊详情页

Identification for Wiener Systems With Internal Noise

时间：0
分类：TP13[自动化与计算机技术—控制科学与工程;自动化与计算机技术—控制理论与控制工程]
作者机构：[1]Key Laboratory of Systems and Control, Institute of Systems Science, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100190, China
相关基金：This research is supported by the National Natural Science Foundation of China under Grant No. 60221301.
相关项目：控制科学中若干关键基础问题的研究

关键词：维纳系统, 维尔斯特拉斯变换, 强连贯性, 循环识别, 内部噪声, Recursive identification, stochastic approximation, strong consistency, Wiener system Weierstrass transformation

中文摘要：

这篇论文考虑内部变量和产量被噪音为贿赂的维纳系统的鉴定。内部噪音什么时候是独立人士并且相等的一个序列，散布了(i 标志) Gaussian 随机的变量，没有内部噪音，由 Weierstrass 转变(WT ) ，在考虑下面的系统转弯是一个维纳系统。后者的非线性的部分不是比原来的系统的非线性的函数的 WT 另外的任何东西，当线性分系统是为在 WT 前后的两个系统的一样时。在合理条件下面，递归的鉴定算法为转变维纳系统被建议，并且为估计的强壮的一致性被建立。由使用反的 WT，为原来的系统的非线性的非参量的估计被导出，并且如果在原来的系统的非线性是一个多项式，他们是强烈历久不渝的。类似的结果也控制内部噪音是 non-Gaussian 的情况。模拟结果与理论分析充分一致。

英文摘要：

This paper considers identification of Wiener systems for which the internal variables and output are corrupted by noises. When the internal noise is a sequence of independent and identically distributed （lid） Gaussian random variables, by the Weierstrass transformation （WT） the system under consideration turns to be a Wiener system without internal noise. The nonlinear part of the latter is nothing else than the WT of the nonlinear function of the original system, while the linear subsystem is the same for both systems before and after WT. Under reasonable conditions, the recursive identification algorithms are proposed for the transformed Wiener system, and strong consistency for the estimates is established. By using the inverse WT the nonparametric estimates for the nonlinearity of the original system are derived, and they are strongly consistent if the nonlinearity in the original system is a polynomial, Similar results also hold in the case where the internal noise is non-Gaussian. Simulation results are fully consistent with the theoretical analysis.