Research on identification method of nonlinear system

doi:10.3778/j.issn.1002-8331.2010.06.006

Computer Engineering and Applications ›› 2010, Vol. 46 ›› Issue (6): 19-22.DOI: 10.3778/j.issn.1002-8331.2010.06.006

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Research on identification method of nonlinear system

XU Xiao-ping^1，2，QIAN Fu-cai¹，WANG Feng^3，4

1.School of Automation and Information Engineering，Xi’an University of Technology，Xi’an 710048，China
2.School of Sciences，Xi’an University of Technology，Xi’an 710054，China
3.State Key Lab for Manufacturing System Engineering，System Engineering Institute，Xi’an Jiaotong University，Xi’an 710049，China
4.School of Sciences，Xi’an Jiaotong University，Xi’an 710049，China

Received:2009-11-10 Revised:2009-12-28 Online:2010-02-21 Published:2010-02-21
Contact: XU Xiao-ping

非线性系统辨识方法研究

徐小平^1，2，钱富才¹，王峰^3，4

1.西安理工大学自动化与信息工程学院，西安 710048
2.西安理工大学理学院，西安 710054
3.西安交通大学系统工程研究所机械制造系统工程国家重点实验室，西安 710049
4.西安交通大学理学院，西安 710049

通讯作者: 徐小平

Abstract

Abstract: A new identification method for nonlinear system based on a wavelet neural network is discussed.In identification process，the parameters of a BP wavelet neural network are trained via an Improved Particle Swarm Optimization（IPSO） algorithm to obtain optimal values to achieve the purpose of identification for the nonlinear system.In numerical simulation，compared with using Standard Particle Swarm Optimization（SPSO） algorithm，the results show that the presented algorithm is obviously improved in the convergence，stability，and so on.

Key words: nonlinear system, identification, wavelet neural network, Particle Swarm Optimization（PSO） algorithm

摘要： 讨论了利用小波神经网络对非线性系统辨识的新方法。在辨识过程中，为了提高小波神经网络对非线性系统的辨识性能，使用一种改进粒子群优化算法对BP小波神经网络参数进行训练，求得最优值，达到对非线性系统辨识目的。在数值仿真中，与采用标准粒子群优化算法相比，结果显示了提出的方法在收敛性和稳定性等方面均得到了明显的改善。

关键词: 非线性系统, 辨识, 小波神经网络, 粒子群优化算法

CLC Number:

TP273

XU Xiao-ping^1，2，QIAN Fu-cai¹，WANG Feng^3，4. Research on identification method of nonlinear system[J]. Computer Engineering and Applications, 2010, 46(6): 19-22.

徐小平^1，2，钱富才¹，王峰^3，4. 非线性系统辨识方法研究[J]. 计算机工程与应用, 2010, 46(6): 19-22.

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Research on identification method of nonlinear system

非线性系统辨识方法研究

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