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
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