Title :
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
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;
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
DOI :
10.1109/WCICA.2008.4594295
