DocumentCode :
3477439
Title :
A Nonlinear Predictive Model Based on Multilayer Perceptron Network
Author :
Li, Huijun ; Ji, Gang ; Ma, Zengliang
Author_Institution :
Chinese Acad. of Sci., Beijing
fYear :
2007
fDate :
18-21 Aug. 2007
Firstpage :
2686
Lastpage :
2690
Abstract :
Predictive model is the foundation of model predictive control algorithm. Most of the model predictive control algorithms applied in practice are based on linear predictive model. But a linear predictive model is not suitable to the process which is highly nonlinear and has long time delay. This paper analyzed the advantages and defects of some nonlinear models and proposed a kind of nonlinear predictive model based on multilayer perceptron network through consulting to NARMAX model and making use of the function approximation capability of multilayer perceptron network. Simulation experiment indicated that the nonlinear predictive model proposed in this paper can excellently predict the output information of a nonlinear system.
Keywords :
function approximation; multilayer perceptrons; neurocontrollers; nonlinear control systems; predictive control; function approximation capability; model predictive control algorithm; multilayer perceptron network; nonlinear predictive model; Automation; Autoregressive processes; Logistics; Multilayer perceptrons; Nonlinear systems; Power engineering and energy; Prediction algorithms; Predictive control; Predictive models; Steady-state; Model Predictive Control; Multilayer Perceptron; NARMAX; Neural Network; Nonlinear System;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Automation and Logistics, 2007 IEEE International Conference on
Conference_Location :
Jinan
Print_ISBN :
978-1-4244-1531-1
Type :
conf
DOI :
10.1109/ICAL.2007.4339035
Filename :
4339035
Link To Document :
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