| 引用本文: | 刘清,岳东.一类有输入噪声扰动的逆系统无偏参数辨识算法研究[J].控制理论与应用,2009,26(9):1031~1034.[点击复制] |
| liu qing,Yue Dong.A class of unbiased identification for inverse system with input noises[J].Control Theory and Technology,2009,26(9):1031~1034.[点击复制] |
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| 一类有输入噪声扰动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 |
| 摘要点击 1763 全文点击 1054 投稿时间：2008-06-17 修订日期：2008-12-11 |
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| DOI编号 10.7641/j.issn.1000-8152.2009.9.CCTA080625 |
| 2009,26(9):1031-1034 |
| 中文关键词 逆系统 参数辨识 输入噪声 偏差消除 |
| 英文关键词 inverse system parameter identification input noise bias-eliminated |
| 基金项目 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). |
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| 中文摘要 |
| 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. |
| 英文摘要 |
| 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 recursive, it can be implemented online for estimating parameters of the inverse system. Experimental results show that the approach is effective. |
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