DocumentCode :
2479855
Title :
Study of How to Identify Nonlinear System Based on Neural Network by MATLAB Toolbox
Author :
Jin Li-qiang ; Yue Weiqiang
Author_Institution :
State Key Lab. of Automotive Simulation, Jilin Univ., Jilin, China
fYear :
2010
fDate :
22-23 May 2010
Firstpage :
1
Lastpage :
4
Abstract :
Aimed at the bulky nonlinear temperature system with time-delay, a DFOPDT model is established. The relation between the classical model and the disperse model of the system is deduced. An algorithm is presented which is an effective way to solve unknown parameters of the model by neural network. The network can soon converge through the iterative calculation in which the value of unknown parameters is predicted continuously. It also solves training a network with unknown output by the function ´train´ in MATLAB neural network toolbox. The system model is identified by the method through step response data, which proves that the method has a good convergence and high accuracy.
Keywords :
delays; identification; mathematics computing; neural nets; nonlinear systems; DFOPDT model; MATLAB toolbox; neural network; nonlinear temperature system; step response data; time-delay; Atmospheric modeling; Automotive engineering; Delay; Electronic mail; Laboratories; MATLAB; Mathematical model; Neural networks; Nonlinear systems; Temperature;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Systems and Applications (ISA), 2010 2nd International Workshop on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-5872-1
Electronic_ISBN :
978-1-4244-5874-5
Type :
conf
DOI :
10.1109/IWISA.2010.5473351
Filename :
5473351
Link To Document :
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