一类有输入噪声扰动动的的逆系统无偏参数辨识算法研究  

A class of unbiased identification for inverse system with input noises

作　　者：刘清[1] 岳东[2] 

机构地区：[1]南京师范大学数学与计算机科学学院,江苏南京210097 [2]南京师范大学电气与自动化学院,江苏南京210042

出　　处：《控制理论与应用》2009年第9期1031-1034,共4页Control Theory & Applications

基　　金：国家自然科学基金资助项目(60774060);江苏省高校自然科学基金资助项目(06KJD520099)

摘　　要：对逆系统建模时,原系统的输出作为逆系统参数辨识时的输入.由于原系统输出存在测量噪声,且噪声方差未知,采用普通最小二乘法辨识,无法得到逆系统参数的一致无偏估计.为此,本文研究了一种有输入扰动的的逆系统无偏参数辨识算法,该算法先通过小波变换估计输入信号噪声的方差,再由估计得到的方差,通过偏差消除的递推最小二乘法,对逆系统的参数进行无偏辨识.该算法降低了对输入辨识信号为白噪声的要求,具有较强的实用性.由于采用递推运算,该算法也可以用于逆系统参数的在线辨识.最后,通过实验验证了该算法的有效性.In identifying the inverse system, the input is the output from the original system. This signal is corrupted by noises with unknown variance. When the ordinary least-squares method is applied to estimate the parameters of the inverse system, the estimates turn out to be biased. A new identification algorithm for bias compensation is proposed. Therein, the noise variance of the inverse system input is first estimated using the wavelet transform and then, a recursive least-squares method with bias-elimination is used to estimate the parameters of the inverse system. Thus, the proposed algorithm does not require the input signal to be the white noise with a zero mean. Since the computation is re.cursive, it can be implemented online for estimating parameters of the inverse system. Experimental results show that the approach is effective.

关 键 词：逆系统 参数辨识 输入噪声 偏差消除 

分 类 号：TP11[自动化与计算机技术—控制理论与控制工程]