An optimizing control strategy for milling circuit operation

Master Thesis

1998

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University of Cape Town

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It has been recognized that significantly more benefit can be derived by operating processes at the economically optimal process conditions than by solely improving the regulatory control performance. This has been the motivation for an increased focus on optimizing control strategies where the set points are adjusted on-line in accordance with an economic criterion. Since plant conditions change, this adjustment needs to be made on a continual basis, but at a frequency lower than that at which inputs are manipulated at the regulatory control level. In the operation of tumbling mills, the fractional filling of the mill with slurry has a marked effect on the efficiency of the breakage process within the mill. The selection of the set point for this variable is critical in the optimization of throughput and energy efficiency in a grinding circuit. Unfortunately, the optimal value for this set point is a function of both circuit and ore characteristics, which means that it varies as the feed and plant characteristics change. This means that periodic re-evaluation of this optimal value needs to be performed in order to fully maximize circuit throughput. The mechanism for seeking this optimum on-line forms the basis for this thesis. Continuous evaluation of the function relating throughput to mill loading (if that were possible) would reveal the optimal set point for the load which could be regularly updated. A recent strategy tackled this issue by assuming power draw from the mill motors is related to circuit, throughput. With the aim to optimize throughput, power consumption can be used as a yardstick by which the load set point (set point for fractional filling in mill) can be selected. The load set point is simply adjusted periodically to optimize the power consumption and correspondingly, the circuit through put. The key proposal in this thesis is a strategy that employs a model of the plant to assist and improve the selection of the load set point.
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Bibliography: pages 97-102.

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