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Description:
The main goal of this project was to develop tuning software for level control of slurry in different Outokumpu flotation cells. Mathematical models were constructed for the first flotation cell, intervening cells and the last cell in the series. A number of models were developed:
The properties of an ideal tank were assumed and classical PI controllers tested, physical properties of the cell (shape) were included, the feedforward control strategy was implemented, dynamics of the Larox pinch valves and Outokumpu Dart-valves were included in the models and the valves were resized, viscosity effect on valve sizing was considered Mathematical models for the double cells were constructed in a similar manner. The principle differences compared with the mathematic models of single cells in series are that, in a double cell, both pulp levels are controlled by manipulating a control valve in the second cell outflow. The simulation of the configurations of three and six TC-50 cells in series resulted in parameters for the PI controllers. All the disturbances introduced into the system could be compensated using both valve sizes.
Different valve sizes and different cell types had an effect on the proportional gain of the PI control: the proportional gains were larger when using valves sized according to the ISA standard than oversized valves. Similarly, the proportional gains were larger in the case of ideal tanks than with cells. Higher proportional gains reduce the settling time of the system in PI control. The Opening speeds (from 0% - 100 %) of the valves have been estimated to be 30 seconds regardless of the valve size, i.e. the bigger the valve, the shorter the rise time.
The influence of valve sizing and additional feed forward control were also studied in a pilot plant. The test configuration consisted of a flotation cell, pulp circulation cell, pulp pump, air feed device and two different control valves. The inflow was measured with magnetic flow meter and the pulp level with a float. The tests were performed with flotation cell with similar geometries (as described above). The results achieved were analogous to those obtained in the simulations. The control performance was noticeably improved by adding the feed forward control. It was also found that an adaptive feed forward control gaincould result in even greater improvements in control performance.
The geometry of the cell had the greatest effect on the performance of the level control. A difference in performance was clearly evident when the same configurations with ideal cells and with different geometry cells were compared. In every case the results were clearly better. Feed forward control implemented with PI control improved the compensation of the disturbances in every case. An adaptive feed forward control gain could result in even bigger improvements in control performance. In future the research extends to determine the effects of recycling flows on the control strategy.
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