DocumentCode :
3734320
Title :
Identification of multivariate system based on PID neural network
Author :
Hua Shu;Xiaogang Wang;Zihang Huang
Author_Institution :
Institute of Mechanical and Electrical Engineering, Guangzhou University, Guangzhou, China
fYear :
2015
Firstpage :
199
Lastpage :
202
Abstract :
System identification is the basis for control system design. For linear time-invariant systems have a variety of identification methods, identification methods for nonlinear dynamic system is still in the exploratory stage. Nonlinear identification method based on neural network is a simple and effective general method that does not require too much priori experience about the system to be identified. Through training and learning, the network weights are corrected to achieve the purpose of system identification. The paper is about the identification of multivariable nonlinear dynamic system based on PID neural network. The structure and algorithm of PID neural network are introduced and the properties and characteristics are analyzed. The system identification is completed and the results are fast convergence.
Keywords :
"Decision support systems","Yttrium","Artificial neural networks","MIMO","Neurons"
Publisher :
ieee
Conference_Titel :
Intelligent Control and Information Processing (ICICIP), 2015 Sixth International Conference on
Print_ISBN :
978-1-4799-1715-0
Type :
conf
DOI :
10.1109/ICICIP.2015.7388168
Filename :
7388168
Link To Document :
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