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隐式GPC算法在重介分选过程控制中的研究
引用本文:曹珍贯,匡亚莉.隐式GPC算法在重介分选过程控制中的研究[J].计算机工程与应用,2014,50(12):6-10.
作者姓名:曹珍贯  匡亚莉
作者单位:1.中国矿业大学 信电学院,江苏 徐州 221116 2.安徽理工大学 电气与信息工程学院,安徽 淮南 232001
基金项目:国家自然科学基金(No.51174202).
摘    要:为解决重介分选过程中重介质悬浮液密度与液位过程模型失配问题,引入隐式GPC算法对模型参数进行在线辨识,实现对重介质悬浮液的密度与液位解耦控制。仿真结果表明,针对重介分选过程模型具有大滞后、强耦合的这一特性,隐式GPC算法控制效果较好,抗干扰能力强,在模型失配的情况下,仍然保持系统的输出稳定。

关 键 词:重介分选  隐式GPC  重介质悬浮液  解耦控制  

Study on implicit GPC in process control of dense medium coal preparation
CAO Zhenguan,KUANG Yali.Study on implicit GPC in process control of dense medium coal preparation[J].Computer Engineering and Applications,2014,50(12):6-10.
Authors:CAO Zhenguan  KUANG Yali
Affiliation:1.School of Information and Electrical Engineering, China University of Mining and Technology, Xuzhou, Jiangsu 221116, China 2.School of Electrical and Information Engineering, Anhui University of Science and Technology, Huainan, Anhui 232001, China
Abstract:In order to solve the model mismatch issue for density and liquid level about heavy medium suspension in the process of dense medium separation, implicit Generalized Predictive Control(GPC)is used to make the on-line identifica-tion for model parameters and realize the decoupling control for density and liquid level. The simulation result shows that for the control model characteristic of large lag and strong coupling control effect based on implicit GPC is better. It has strong anti-interference capability, and the system output is still stable in the case of model mismatch.
Keywords:dense medium coal preparation  implicit Generalized Predictive Control(GPC)  dense medium suspension  decoupling control
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