Predictive control with fuzzy characterization of percentage of solids, particle size and power demand for minerals grinding

M. Orchard, A. Flores, C. Muñoz, A. Cipriano
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引用次数: 3

Abstract

The application of fuzzy predictive control to solve the regulatory problem in mineral grinding plants is considered. The controlled variables are percentage of solids, particle sizes and power demand and the manipulated variables are water and fresh ore flows. The controller uses linear multivariable models and the fuzzy characterization of the controlled variables, to calculate the manipulated variables. Simulation results under typical disturbances show a better performance compared with the conventional predictive control.
预测控制与模糊表征的固体百分比,粒度和电力需求的矿物研磨
研究了模糊预测控制在解决选矿厂控制问题中的应用。控制变量是固体的百分比,颗粒大小和电力需求,操纵变量是水和新鲜矿石流量。该控制器采用线性多变量模型和被控变量的模糊表征,计算被控变量。在典型干扰下的仿真结果表明,与传统预测控制相比,该方法具有更好的控制性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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