基于组合式信号源的非线性系统辨识

doi:10.16182/j.issn1004731x.joss.21-0589

系统仿真学报 ›› 2022, Vol. 34 ›› Issue (11): 2377-2385.doi: 10.16182/j.issn1004731x.joss.21-0589

基于组合式信号源的非线性系统辨识

郑天¹(), 李峰¹(), 贺乃宝¹, 顾亚²

^1.江苏理工学院　电气信息工程学院，江苏　常州　213001
^2.上海师范大学　信息与机电工程学院，上海　201418

收稿日期:2021-06-25 修回日期:2021-08-20 出版日期:2022-11-18 发布日期:2022-11-25
通讯作者: 李峰 E-mail:769447368@qq.com;lifeng@jsut.edu.cn
作者简介:郑天(1995-)，男，硕士生，研究方向为块结构模型辨识。E-mail：769447368@qq.com
基金资助:
国家自然科学基金(62003151);江苏省自然科学基金(BK20191035);常州市科技计划(CJ20220065)

Nonlinear System Identification Based on Combined Signal Sources

Tian Zheng¹(), Feng Li¹(), Naibao He¹, Ya Gu²

^1.College of Electrical and Information Engineering, Jiangsu University of Technology, Changzhou 213001, China
^2.College of Information, Mechanical and Electrical Engineering, Shanghai Normal University, Shanghai 201418, China

Received:2021-06-25 Revised:2021-08-20 Online:2022-11-18 Published:2022-11-25
Contact: Feng Li E-mail:769447368@qq.com;lifeng@jsut.edu.cn

摘要/Abstract

摘要：

针对非线性系统中噪声的干扰，研究了一类神经模糊Hammerstein输出误差非线性系统的建模和辨识方法，利用组合式信号源实现静态非线性模块和动态线性模块参数辨识的分离，推导了相关性分析法和辅助模型递推最小二乘辨识方法估计动态线性模块和非线性模块的参数，有效抑制系统输出噪声的干扰。仿真结果表明：与最小二乘算法、多项式模型以及多信息方法相比，提出的方法具有参数估计收敛速度快，辨识精度高，建模误差小等优势，验证了所提学习算法的有效性。

关键词: Hammerstein非线性系统, 辨识建模, 组合式信号源, 相关性分析法

Abstract:

Aiming at the interference of noise in the nonlinear system, the identification modeling method of the neuro-fuzzy Hammerstein output error nonlinear system is considered. The combined signal sources are used to realize the parameter identification separation of the linear block and the nonlinear block. The correlation analysis method and the recursive least square identification method based on auxiliary model technique are derived to estimate the parameters of dynamic linear block and nonlinear block, which can effectively suppress the interference of system output noise. Compared with least square algorithm, polynomial model and multi-innovation method, the simulation results demonstrate that the proposed approach has the advantages of fast convergence speed of parameter estimation, high identification accuracy and small modeling error, which verifies the effectiveness of the proposed approach.

Key words: Hammerstein nonlinear system, identification modeling, combined signal sources, correlation analysis method

中图分类号:

郑天, 李峰, 贺乃宝, 顾亚. 基于组合式信号源的非线性系统辨识[J]. 系统仿真学报, 2022, 34(11): 2377-2385.

Tian Zheng, Feng Li, Naibao He, Ya Gu. Nonlinear System Identification Based on Combined Signal Sources[J]. Journal of System Simulation, 2022, 34(11): 2377-2385.

图/表 8

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参考文献 31

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方法	阶次	MSE	MAE
多项式法	9	1.8×10^‒3	1.165 5
	10	7.9×10^‒4	0.812 5
	11	4.6×10^‒4	0.416 5
	12	3.7×10^‒3	1.398 7
本文所提方法		2.298 6×10^‒4	0.227 4

基于组合式信号源的非线性系统辨识

Nonlinear System Identification Based on Combined Signal Sources

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