Study of Improved Generalized Predictive Control in Ball Mill Application

doi:10.16182/j.cnki.joss.2015.06.026

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.

Key words: ball mill, generalized predictive control, automatic control, control method

CLC Number:

TP391.9

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

References

[1] 王恒,贾民平,许飞云,等.基于FKCM的球磨机系统TS模糊建模方法[J].系统仿真学报,2009, 21(2): 530-533.
(Wang Heng, Jia Minping, Xu Feiyun, et al. FKCM ball mill system based on TS fuzzy modeling method[J]. Journal of System Simulation (SI004-73IX), 2009,21(2): 530-533.)
[2] 席裕庚,李德伟,林姝.模型预测控制一现状与挑战[J].自动化学报,2013, 39(3): 222-236.
[3] Sato T.Design of a GPC-based PID Controller for Controlling a Weigh Feeder[J]. Control engineering practice (S0967-0661), 2010, 18(2): 105-113.
[4] Sato T, Inoue A.GPC-based PID Controller Using a Stable Time-varying Proportional Gain[C]// Networking, Sensing and Control (SI810-7869), 2007 IEEE International Conference on. USA: IEEE, 2007: 536-541
[5] Yamamoto T, Yamada T, Fujii T, et al. Design and Implementation of a GPC-based Auto-tuning PID Controller[C]// Industrial Technology (S0780378520), 2006. ICIT 2006. IEEE International Conference on. USA: IEEE, 2006: 1920-1924.
[6] Sato T, Kotarii T, Yamamoto T, et al. Design of a Performance-adaptive GPC-PI Control System for Controlling a Weigh Feeder[C]// Control Applications (CCA)(SI 085-1992), 2012 IEEE International Conference on. USA: IEEE, 2012: 521-525.
[7] Pengzhan C, Baifen L.Combined PI and GPC for Servo System[C]// Computer, Mechatronics, Control and Electronic Engineering (CMCE)(S9781424479573), 2010 International Conference on. USA: IEEE, 2010, 4: 254-257.
[8] Ai-Xian P, Guang-Yi W, Dong H.Control of Permanent Magnet Synchronous Motor Based on GPC[C]// Wireless Communications, Networking and Mobile Computing (S9781424421077), 2008. WiCOM^S. 4th International Conference on. USA: IEEE, 2008: 1-4.
[9] 薛美盛,樊弟,魏衡华.多变量系统的广义预测控制解耦设计[J]•控制工程,2011, 18(1): 39-42.
[10] 李瑞瑞. 基于粒子群算法的广义预测控制及其应用研究[D].兰州:兰州交通大学,2012
[11] Su Z, Wang P,Yu 又 Immune Genetic Algorithm-based Adaptive Evidential Model for Estimating Unmeasured Parameter: Estimating levels of coal powder filling in ball mill[J]. Expert Systems with Applications (S0957-4174), 2010, 37(7): 5246-5258.
[12] 时域,郭伟,王伟.PID型广义预测控制在过热温控中的应用[J].计算机工程:(S1000-3428),2009, 35(11): 251-253.
[13] 陶文华,柴天佑,岳恒.钢球磨煤机的动态参数模型与仿真研究[J].系统仿真学报,2004, 16(4): 778-780.
[14] 梁兆阳,孙建平,孙静.BP神经网络PBD控制器在球磨机控制中的应用[J].伩器仪表用户,2008,15(2): 42-43.
[15] 綦守荣,王东风,韩璞,等.基于鲁棒整定的球磨机系统多变量PBD控制[J].系统仿真学报,2006, 17(12) 3001-3003.
(Qi Shourong, Wang Dongfeng, Han Pu, et al. Tuning ball mill system based on robust multivariable PID control [J]. Journal of System Simulation (S1004-73IX), 2006, 17(12): 3001-3003.).