Study of Improved Generalized Predictive Control in Ball Mill Application

Authors

Lingfang Sun, School Of Automation Engineering,Northeast Dianli University, Jilin 132012, China;
Jingmiao Sun, School Of Automation Engineering,Northeast Dianli University, Jilin 132012, China;

Abstract

Abstract: Direct-fired pulverizing system with double inlets and outlets is regarded as important generating equipment in power plant, which has characteristics of nonlinear, multivariable, strong coupling and time-varying. Started from the mechanism of law, the mechanism mathematical model of the ball mill was established and a certain amount of disturbance transfer ftinction model was added in a mathematical model of the mechanism of input variables to give step disturbance tests to establish the ball mill system. Combining the most widely used basic control--PID control as industrial process control, and on the basis of general generalized predictive control algorithm, the generalized predictive control algorithm with a proportional-integral-derivative structure (PID-GPC) was applied to the ball mill. Through a 300 MW power unit negative run large ball mill pulverizing system simulation in Longshan, Hebei, China, it is shown that the algorithm has better robustness than general feed-forward decoupling PID control, and it^Js better to be applied in industry.

Recommended Citation

Sun, Lingfang and Sun, Jingmiao (2021) "Study of Improved Generalized Predictive Control in Ball Mill Application," Journal of System Simulation: Vol. 27: Iss. 6, Article 26.
DOI: 10.16182/j.cnki.joss.2015.06.026
Available at: https://dc-china-simulation.researchcommons.org/journal/vol27/iss6/26

First Page

1329

Revised Date

2014-09-18

DOI Link

https://doi.org/10.16182/j.cnki.joss.2015.06.026

Last Page

1337

CLC

TP391.9

Recommended Citation

Sun Lingfang, Sun Jingmiao. Study of Improved Generalized Predictive Control in Ball Mill Application[J]. Journal of System Simulation, 2015, 27(6): 1329-1337.

DOI

10.16182/j.cnki.joss.2015.06.026