Title :
Model identification of time-delay nonlinear system with FIR neural network
Author :
Wang, Li-feng ; Li, Zheng-xi
Author_Institution :
Field Bus Tech & Autom. Lab, North China Univ. of Technol., Beijing, China
Abstract :
The FIR neural network model and its temporal backpropagation algorithm are introduced in this paper. Due to its time-delay dynamic characteristics, it is fit well to be applied to model identification of the time-delay nonlinear system. Model identification has been completed successfully on actual datasets of 6 stands tandem hot mill with FIR neural network, and the results show its good characteristics.
Keywords :
FIR filters; backpropagation; delays; hot rolling; identification; milling; neural nets; nonlinear control systems; rolling mills; FIR neural network; tandem hot mill; temporal backpropagation algorithm; time-delay dynamic characteristics; time-delay nonlinear system; Backpropagation algorithms; Biological system modeling; Cost function; Finite impulse response filter; Milling machines; Neural networks; Neurons; Nonlinear filters; Nonlinear systems; Sequences;
Conference_Titel :
Machine Learning and Cybernetics, 2003 International Conference on
Print_ISBN :
0-7803-8131-9
DOI :
10.1109/ICMLC.2003.1259601
