MPC for Simple Setup of Mid-Range and Other Advanced Controls, 19PaperCon

Multivariable model predictive control (MPC) has demonstrated good performance in both cross-direction and machine-direction applications and is a control strategy of choice in many mills. MPC uses process models to make predictions of future output trajectories based on past and planned input moves. MPC plans an optimal sequence of moves based on a cost function which typically penalizes both output deviations from setpoints and input moves. Since the process models are built into the controller, the movements of all inputs are coordinated to minimize output disturbances due to multivariable interactions. 

Output deviations and input movements are not the only costs that may be included in the cost function. It is also possible to penalize deviations of process inputs from preferred values, which is useful in several situations including midrange control, where two process inputs can control one output. Examples of midrange control include coarse and fine stock valves for stock flow control or upstream and downstream filler flows. In midrange control the first input makes fast and/or accurate adjustments to keep the process on target while the second input makes slower and/or coarse adjustments that allow the first input to stay near a preferred value. 

Midrange control can be implemented quickly and easily using an MPC that allows penalties on deviations of inputs from preferred targets. This paper describes midrange control for filler flow addition implemented at a North American fine paper mill. The MPC framework allows the controller to be tuned so that the fast-acting filler flow quickly eliminates disturbances to ash while corrections are also made with the slower acting filler flow so that, in the long term, the fast-acting filler flow can return to a preferred value and ash remains on target. Results from the mill implementation will be given. 

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