一类有色噪声干扰随机系统最小二乘递推辨识

王冬青

一类有色噪声干扰随机系统最小二乘递推辨识

王冬青

青岛大学自动化工程学院, 青岛 266071

基金项目: 国家自然科学基金资助项目(60673101)

详细信息

作者简介:
王冬青(1964-),女,山东即墨人,副教授,dqwang64@163.com.

中图分类号: TP 273
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- 被引次数: 0
出版历程
- 收稿日期: 2007-12-03
- 网络出版日期: 2008-08-31

Least squares based recursive identification for stochastic systems with colored noises

Wang Dongqing

College of Automation Engineering, Qingdao University, Qingdao, 266071, China

摘要

摘要: 提出一类有色噪声干扰随机系统的辅助模型最小二乘递推辨识算法.此算法结合辅助模型辨识思想和递推增广最小二乘理论,用辅助模型的输出代替辨识模型信息向量中未知中间变量,用估计残差代替信息向量中不可测噪声项,从而可以运用递推辨识思想来估计系统所有参数,包括噪声模型参数.仿真例子说明提出算法的有效性.
- 递推辨识 /
- 参数估计 /
- 最小二乘 /
- 随机系统
Abstract: An auxiliary model and least squares based recursive identification algorithm was presented for stochastic systems with colored noises. The basic idea is, by means of the auxiliary model identification principle and extended least squares identification theory, to replace the unknown variables in the information vector with the outputs of the auxiliary model and to replace the unmeasurable noise terms with the estimated residuals, and then to propose a recursive identification algorithm to estimate all parameters of the systems, including the parameters of the noise models. The simulation results indicate that the algorithm is effective.
- recursive identification /
- parameter estimation /
- least squares /
- stochastic systems

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参考文献(1)

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