Abstract
In this paper the control performance of the flotation process is evaluated as a function of the measurement accuracy and sampling frequency of an on-stream analyzer. First, the performance of rule-based control and model predictive control (MPC) strategies is studied using discrete flotation models and the respective performance indices. Next, the net smelter return (NSR) is calculated for varying sampling rate and accuracy combinations using the PI controllers-based control strategy, mechanistic flotation models and the industrial process data as input. The control and economical performance of the process declines strongly when the sampling cycle is increased. The results also indicate that the speed of on-line analysis has a significant effect on the production economics, calculated as the average net smelter return.
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