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Author Kashiwagi, H. ♦ Harada, H. ♦ Li Rong
Source IEEE Xplore Digital Library
Content type Text
Publisher Institute of Electrical and Electronics Engineers, Inc. (IEEE)
File Format PDF
Copyright Year ©2002
Language English
Subject Domain (in DDC) Technology ♦ Engineering & allied operations ♦ Other branches of engineering
Subject Keyword Kernel ♦ Nonlinear systems ♦ Computer simulation ♦ Linear systems ♦ Neural networks ♦ Fuzzy neural networks ♦ Extrapolation
Abstract This paper describes a method for identifying and separating Volterra kernels of nonlinear control systems by use of pseudorandom M-sequence and correlation technique. By use of this method, we can obtain Volterra kernels of up to 3rd order of a nonlinear system. M-sequence is applied to a nonlinear system and the crosscorrelation function between the input and output is calculated. Then the crosscorrelation function includes all the crosssections of Volterra kernels of the nonlinear system. The problem is how to separate these crosssections from each other. This paper proposes two methods for this purpose. One is the method of suitable selection of M-sequence which enables us to separate crosssections each other. The other is the use of amplitude variation method. Computer simulations show that this method for identification and separation of Volterra kernels of nonlinear system is very effective for identifying nonlinear control systems.
Description Author affiliation: Fac. of Eng., Kumamoto Univ., Japan (Kashiwagi, H.; Harada, H.; Li Rong)
ISBN 0780376315
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research ♦ Reading
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2002-08-05
Publisher Place Japan
Rights Holder SICE
Size (in Bytes) 340.75 kB
Page Count 6
Starting Page 707
Ending Page 712


Source: IEEE Xplore Digital Library