Multivariable Control and Energy Optimization of Tissue Machines, PaperCon '09 Conference

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The desire to increase profits by minimizing operating costs without sacrificing paper quality and runability is a goal all papermakers strive for. Modern tissue machines are typically equipped with more than twenty low-level control loops and multiple sheet property measurements at various locations along the machine. It is a large and strongly coupled process that can be difficult for control engineers to optimize without advanced multivariable control techniques.

This paper examines the process interactions and energy cost reductions using model predictive control (MPC) technology with an optimization layer that automatically drives the process towards the lowest cost while honoring hard process and quality constraints. The studied paper machine was equipped with a fast scanning moisture measurement before the Yankee dryer in addition to the measurements of a traditional reel scanner.

Author: Stephen Chu, Ross MacHattie, and Johan Backstrom
Multivariable Control and Energy Optimization of Tissue Mach
Multivariable Control and Energy Optimization of Tissue Machines, PaperCon '09 Conference
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