Temperature prediction based on PSO and SVM for Roller hearth Heat Treatment Furnace

Author

Li, Jing ; Wang, Jing

Author_Institution

Eng. Res. Inst., Univ. of Sci. & Technol. Beijing, Beijing, China

Volume

8

fYear

2010

fDate

10-12 Aug. 2010

Firstpage

4327

Lastpage

4330

Abstract

In this paper, a new nonlinear system prediction control algorithm is proposed according to the process requirements of Roller-hearth Heat Treatment Furnace. The new control algorithm uses particle swarm optimization (PSO) and support vector machine (SVM) to establish the predictive model. This model is established and simulated using lots of data acquired from the site. The result indicates that this prediction model based on PSO and SVM has can raise the precision of furnace temperature. It is proved that this model has good application future.

Keywords

furnaces; heat treatment; nonlinear control systems; particle swarm optimisation; production control; production engineering computing; support vector machines; temperature control; nonlinear system prediction control algorithm; particle swarm optimization; roller hearth heat treatment furnace; support vector machine; temperature prediction; Furnaces; Heat treatment; Kernel; Optimization; Prediction algorithms; Predictive models; Support vector machines; PSO(particle swarm optimizer algorithm); SVM(support vector machine); predictive control; roller-hearth heat treatment furnace;

fLanguage

English

Publisher

ieee

Conference_Titel

Natural Computation (ICNC), 2010 Sixth International Conference on

Conference_Location

Yantai, Shandong

Print_ISBN

978-1-4244-5958-2

Type

conf

DOI

10.1109/ICNC.2010.5583608

Filename

5583608