Research on multi-signal based neuro-fuzzy Hammerstein-Wiener model

被引：0
作者：
Jia, Li [1 ]
Yang, Ai-Hua [1 ]
Chiu, Min-Sen [2 ]
机构：
[1] Department of Automation, College of Mechatronics Engineering and Automation, Shanghai University
[2] Faculty of Engineering, National University of Singapore
来源：
Zidonghua Xuebao/Acta Automatica Sinica | 2013年 / 39卷 / 05期
关键词：
Hammerstein-Wiener model; Neuro-fuzzy systems; Nonlinear systems; Signal separation;
D O I：
10.3724/SP.J.1004.2013.00690
中图分类号：
学科分类号：
摘要：
In order to solve the control problem of complex systems, it is important to design a special structure model with data information to simplify the question of designing control system. Thus, a multi-signal based neuro-fuzzy Hammerstein-Wiener model is proposed, which breaks through the traditional iterative separation method. The separation of the neuro-fuzzy nonlinear and linear parts of the Hammerstein-Wiener model is realized by one kind of multi-signals. And a noniterative neuro-fuzzy optimization algorithm is designed to expand the research results to piecewise nonlinear system, which can be applied to much more nonlinear systems. This algorithm guarantees the precision of the model. Moreover, it has the ability of approximating strong nonlinearity. Furthermore, a neuro-fuzzy Hammerstein-Wiener model based control system is designed to simplify the control problem of the nonlinear system into the problem of linear system by using the special structure of the model. As a result, the traditional PID controller can get a better control result. Simulated results show the effectiveness of the method. Copyright © 2013 Acta Automatica Sinica. All rights reserved.
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页码：690 / 696
页数：6
相关论文
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