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传递函数辨识(18): 输出误差模型的辅助模型递阶迭代参数估计

作者:时间:2021-03-18点击数:

全文下载: 202101001.pdf


文章编号: 16726987202101000113 DOI 10.16351/j.16726987.2021.01.001


丁锋1,2, 刘喜梅2(1.江南大学 物联网工程学院,江苏 无锡 214122; 2.青岛科技大学 自动化与电子工程学院,山东 青岛 266061)


摘要: 针对输出误差系统,利用迭代搜索原理,研究了辅助模型梯度迭代算法、辅助模型最小二乘迭代算法、辅助模型多新息梯度迭代算法、辅助模型多新息最小二乘迭代算法;利用递阶辨识原理,研究了辅助模型递阶梯度迭代算法、辅助模型递阶多新息梯度迭代算法、辅助模型递阶最小二乘迭代算法、辅助模型递阶多新息最小二乘迭代算法等。这些辨识方法可以推广到有色噪声的随机系统中。

关键词: 参数估计; 迭代辨识; 辅助模型辨识; 多新息辨识; 递阶辨识


中图分类号: TP 273文献标志码: A

引用格式: 丁锋, 刘喜梅. 传递函数辨识(18): 输出误差模型的辅助模型递阶迭代参数估计[J. 青岛科技大学学报(自然科学版), 2021, 42(1): 113.

DING Feng, LIU Ximei. Transfer function identification. Part R: Auxiliary model hierarchical iterative parameter estimation for outputerror modelsJ. Journal of Qingdao University of Science and TechnologyNatural Science Edition), 2021 421): 113.


Transfer Function Identification. Part R: Auxiliary Model Hierarchical Iterative

Parameter Estimation for OutputError Models


DING Feng1,2, LIU Ximei2

(1.School of Internet of Things Engineering, Jiangnan University, Wuxi 214122, China;

2.College of Automation and Electronic Engineering, Qingdao University of Science and Technology, Qingdao 266061, China)


Abstract: For outputerror models, this paper presents the auxiliary model gradientbased iterative algorithm, the auxiliary model least squaresbased iterative algorithm, the auxiliary model multiinnovation gradientbased iterative algorithm, and the auxiliary model multiinnovation least squaresbased iterative algorithm based on the gradient search principle, and presents the auxiliary model hierarchical gradientbased iterative algorithm, the auxiliary model hierarchical least squaresbased iterative algorithm, the auxiliary model hierarchical multiinnovation gradientbased iterative algorithm, and the auxiliary model hierarchical multiinnovation least squaresbased iterative algorithm based on the hierarchical identification principle, These methods can be extended to stochastic outputerror systems with colored noises.

Key words: parameter estimation; iterative identification; auxiliary model identification; multiinnovation identification; hierarchical identification


收稿日期: 20201212

基金项目: 国家自然科学基金项目(61873111).

作者简介: 丁锋(1963—),男,博士,泰山学者特聘教授,博士生导师.




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