Machine Direction Adaptive Control on a Paper Machine

Abstract

Control of industrial sheet and film processes involves separate controllers and actuators for minimizing both temporal variations along the machine direction (MD) and spatial variations along the cross direction (CD). Model-based control methods such as model predictive control (MPC) have gained widespread implementation for controlling both the MD and CD processes. One limitation of model-based methods is that changes in the true process pose significant identification challenges for operators which are often resolved with costly open loop identification experiments. The predominant industrial measurement technology acquires a signal of mixed MD and CD variations that requires separation. This work compares various model-free approaches for MD-CD separation as a prerequisite to effective MD control. To address the challenges of model-based control, this paper introduces an adaptive control method for the MD process. Closed loop identification experiments are conducted and compared to benchmarks on an industrial paper machine simulator.