引用本文:马天雨,桂卫华.铝土矿连续磨矿过程球磨机优化控制[J].控制理论与应用,2012,29(10):1339~1347.[点击复制]
MA Tian-yu,GUI Wei-hua.Optimal control for continuous bauxite grinding process in ball-mill[J].Control Theory and Technology,2012,29(10):1339~1347.[点击复制]
铝土矿连续磨矿过程球磨机优化控制
Optimal control for continuous bauxite grinding process in ball-mill
摘要点击 2449  全文点击 1345  投稿时间:2011-12-18  修订日期:2012-04-19
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DOI编号  10.7641/j.issn.1000-8152.2012.10.CCTA111451
  2012,29(10):1339-1347
中文关键词  磨矿过程  多模型预测控制  多目标优化  区间控制  乘子罚函数
英文关键词  mineral grinding process  multiple model predictive control  multiple objective optimization  interval control  multiplier penalty function
基金项目  国家自然科学基金资助项目(61134006, 61273187); 新世纪优秀人才支持计划资助项目(NCET-08-0576).
作者单位E-mail
马天雨* 中南大学 信息科学与工程学院 pymty@yahoo.com.cn 
桂卫华 中南大学 信息科学与工程学院  
中文摘要
      针对铝土矿连续磨矿过程球磨机节能降耗问题以及铝土矿来源复杂、品位差异大等特点, 提出了球磨机多目标多模型预测控制方法. 该方法首先建立状态空间浓度预测模型和粒级质量平衡加权多模型细度预测模型. 然后构建了包含磨机排矿浓细度区间控制和经济性能指标的多目标优化结构的多模型预测控制策略. 最后采用乘子罚函数法求解控制器局部最优解. 仿真及现场试验结果表明了该方案的有效性.
英文摘要
      Considering the reduction of power consumption of ball-mill, we propose a multi-objective multi-model predictive control for the continuous grinding process of bauxite with bauxite ores coming from different mine sources and with different qualities. In this method, we first build the state-space concentration-predictive model and the finenessprediction model based on the weighted multi-model of size-mass balance; and then, we develop an optimal multi-model predictive control scheme for optimizing multiple objectives including the interval control of concentration and fineness of the discharged ore pulp from the ball-mill, along with economic indices. The local optimal control law of the controller is obtained by minimizing a multiplier penalty function. The simulation and the field test results show the effectiveness of this method.