Modelling and identifications of basis weight variations in paper machines

A dynamic model for basis weight variations in paper machines is established and estimated recursively from scanned measurements using a combination of an exponential forgetting and resetting least squares estimator and an extended Kalman filter. The algorithm provides online estimation of basis weight variations in both cross-machine direction and machine direction, as well as estimates of the dynamic parameters and noise characteristics of the process. >