DocumentCode
499006
Title
Design of blender IMC control system based on simple recurrent networks
Author
Du, Yun ; Sun, Hui-qin ; Tian, Qiang ; Zhang, Su-Ying ; Wang, Chang
Author_Institution
Hebei Univ. of Sci. & Technol., Shijiazhuang, China
Volume
2
fYear
2009
fDate
12-15 July 2009
Firstpage
1048
Lastpage
1052
Abstract
Blender is the key tache in the production process of foodstuff and chemistry and so on. The material control value has a complicated non-linear relationship with the flux value. It is difficult to build the accurate mathematical model by traditional method. The internal model control (IMC) system based on the simple dynamic recurrent neural network (SRNN) is presented in this paper. It is very simple because of the recursion layer without the weight values in SRNN, and the regulated network parameters is very few. The control system based on SRNN is composed of the positive model, the inverse model and the filter. The simulation shows that the system has the better anti- disturbing capability. It can satisfy the rapidness and the veracity of control system. It can be used in real time.
Keywords
blending; control system synthesis; production engineering computing; recurrent neural nets; antidisturbing capability; blender IMC control system; dynamic recurrent neural network; flux value; internal model control; inverse model; material control value; mathematical model; nonlinear relationship; production process; simple recurrent networks; Chemistry; Control systems; Convergence; Cybernetics; Feedforward neural networks; Feeds; Machine learning; Neural networks; Nonlinear dynamical systems; Recurrent neural networks; Blender; Dynamic recurrent neural network; Internal model control;
fLanguage
English
Publisher
ieee
Conference_Titel
Machine Learning and Cybernetics, 2009 International Conference on
Conference_Location
Baoding
Print_ISBN
978-1-4244-3702-3
Electronic_ISBN
978-1-4244-3703-0
Type
conf
DOI
10.1109/ICMLC.2009.5212450
Filename
5212450
Link To Document