| Summary: | Paper coating is the process of applying coating colour or functional materials to the surface
of paper. The goal of coating is to improve the surface quality of the paper. In this thesis, the
bevelled-blade coating process is modeled based on the force equilibrium at the tip of the blade
using fluid mechanic principles. The effects of the factors influencing coating weight are analyzed
using simulation results. Mill trials have been carried out to investigate the dynamics of the coating
process and the interaction of the cross machine profilers. Machine-direction (MD) and cross-direction
(CD) variations were estimated using an algorithm previously developed at the University of British
Columbia. Coating weight variations were studied and possible achievements were indicated. From
the estimated cross-direction profiles, the amplitude and width of the profile response to the bump
test were analyzed, and then used to build the interaction model of CD actuators.
The goals of both the machine-direction and the cross-direction coating weight controls are to
improve the uniformity of coating weight Due to the advantages of Generalized Predictive Control,
both MD and CD control loops are designed using adaptive constrained GPC. The machine-direction
coating weight process is modeled as a first-order system with a time-varying gain defined by the
nonlinear relationship between coating weight and the control variable. The time-varying parameters
are estimated by the recursive least-squares (RLS) method with exponential forgetting and resetting
factors. The cross-direction coating process is also modeled as a first-order system with a nonlinear
gain determined by the relationship between the local blade pressure and the coating weight Based
on the interaction of CD actuators, the interaction matrix of the first-order model is defined as a
band-diagonal matrix. Multi-input, single-output RLS estimators are developed to perform on-line
parameter estimation. Constraints on the control signal are considered in response to the limits of the
industrial settings. The optimal solutions to both constrained univariate and multivariable GPC are
obtained using the Lagrangian multiplier method. Simulation studies are carried out to evaluate the
performance of the adaptive constrained GPC. The results of the simulations show that the controllers
can track the set-point changes closely, while rejecting the disturbance and handling the model plant
mismatch well. === Applied Science, Faculty of === Electrical and Computer Engineering, Department of === Graduate
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