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首页> 外文期刊>Journal of Process Control >Combined fuzzy based feedforward and bubble size distribution based feedback control for reagent dosage in copper roughing process
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Combined fuzzy based feedforward and bubble size distribution based feedback control for reagent dosage in copper roughing process

机译:基于模糊前馈和气泡尺寸分布的反馈控制相结合的铜粗加工试剂用量

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摘要

A combined fuzzy based feedforward (FBF) and bubble size distribution (BSD) based feedback reagent dosage control strategy is proposed to implement the product indices in copper roughing process. A fuzzy theory based feedforward compensator will be used to calculated the reagent dosage in advance to eliminate the influence of large disturbances according to ore grade and handling capacity. Since the bubble size is believed to be closely related to flotation performance and responds to changes in the reagent dosage, using BSD based feedback predictive control calculates the reagent dosage to stabilize the flotation running. Instead of simple statistic feature, the bubble size with non-Gaussian feature is characterized to be probability density function (PDF) by using B-spline. A multi-output least square support vector machine (MLS-SVM) based is then applied to establish a dynamical relationship between the weights of B-spline and the reagent dosage since the weights are interrelated and related to the reagent dosage. A multiple step based optimization algorithm is finally proposed to determine the reagent dosage. Experimental results can show the effectiveness of the proposed method. (C) 2015 Elsevier Ltd. All rights reserved.
机译:提出了一种基于模糊前馈(FBF)和气泡尺寸分布(BSD)的反馈试剂剂量控制策略,以实现铜粗加工过程中的产品指标。基于模糊理论的前馈补偿器将根据矿石品位和处理量预先计算试剂用量,以消除较大干扰的影响。由于气泡大小被认为与浮选性能密切相关并且对试剂剂量的变化做出响应,因此使用基于BSD的反馈预测控制来计算试剂剂量以稳定浮选运行。通过使用B样条,具有非高斯特征的气泡大小代替简单的统计特征而被表征为概率密度函数(PDF)。然后,基于多输出最小二乘支持向量机(MLS-SVM)来建立B样条的权重和试剂剂量之间的动力学关系,因为这些权重是相互关联的并且与试剂剂量相关。最后提出了一种基于多步骤的优化算法来确定试剂用量。实验结果表明了该方法的有效性。 (C)2015 Elsevier Ltd.保留所有权利。

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