Intelligent control for moisture of sinter mixture based on ABPM artificial neural network

Author

Li, Guo ; Zhang, Guangming ; Ling, Xiang ; Gui, Weihua ; Tang, Guizhong

Author_Institution

Coll. of Autom., NanJing Univ. of Technol., Nanjing

fYear

2008

fDate

25-27 June 2008

Firstpage

8676

Lastpage

8680

Abstract

The moisture control for sinter mixture is always a difficulty in industry. This paper presents a modeling for the Pb-Zn sintering process of Imperial Smelting Process(ISP), which is to solve the modeling of permeability and parameters of sintering technical. An intelligent system for controlling moisture of sinter mixture based on ABPM artificial neural network is developed for the purpose. The BP network is trained by adaptive variable step size algorithm in order to get high accuracy and fast convergence speed.Theoretical research and simulation verify the effectiveness of the proposed method.

Keywords

adaptive control; moisture control; neurocontrollers; permeability; sintering; smelting; ABPM artificial neural network; adaptive variable step size algorithm; imperial smelting process; intelligent control; intelligent system; moisture control; sinter mixture; sintering process; Artificial intelligence; Artificial neural networks; Electrical equipment industry; Industrial control; Intelligent control; Intelligent networks; Intelligent systems; Moisture control; Permeability; Smelting; adaptive variable step size algorithm; artificial neural network; moisture of mixture; permeability;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Control and Automation, 2008. WCICA 2008. 7th World Congress on

Conference_Location

Chongqing

Print_ISBN

978-1-4244-2113-8

Electronic_ISBN

978-1-4244-2114-5

Type

conf

DOI

10.1109/WCICA.2008.4594295

Filename

4594295