Research and application of neural network PID control in cement industry

Author

Yao, Zheng ; Li, Xiaoying ; Wang, Zhaohua

Author_Institution

Coll. of Comput. & Autom. Control, Hebei Polytech. Univ., Tangshan, China

Volume

2

fYear

2010

fDate

10-11 July 2010

Firstpage

424

Lastpage

427

Abstract

As various parameters of cement rotary kiln temperature control system means the relationships of strong coupling, nonlinearity and fast time-variety, there are many factors impact the temperature of combustion. Aiming at the constant control, an improved PID control method based on RBF neural network is proposed, and a new model of temperature intelligent controller to control nonlinear systems for multi-variable control was presents in the paper. Mathematical model of RBFNN PID controller was built, and the control simulation of entire model is realized by Matlab. The result of simulation indicates that the improved control algorithm offers better control effects than traditional PID control.

Keywords

cement industry; cements (building materials); combustion; control engineering computing; kilns; neurocontrollers; production engineering computing; radial basis function networks; temperature control; three-term control; Matlab; RBF neural network; RBFNN PID controller; cement industry; cement rotary kiln temperature control system; combustion temperature; constant control; control algorithm; control simulation; coupling; multivariable control; neural network PID control; nonlinear control systems; temperature intelligent controller; Atmospheric modeling; Jacobian matrices; MATLAB; Mathematical model; Predictive models; Process control; Target tracking; PID; cement rotary kiln; neural network;

fLanguage

English

Publisher

ieee

Conference_Titel

Industrial and Information Systems (IIS), 2010 2nd International Conference on

Conference_Location

Dalian

Print_ISBN

978-1-4244-7860-6

Type

conf

DOI

10.1109/INDUSIS.2010.5565743

Filename

5565743