Modelling and identification of paper machine wet end chemistry

Chemicals are added in the wet end of a paper machine to control operability and/or quality measures such as retention, drainage, sheet strength, etc. Current understanding of the effects of such additives in a mill environment is generally restricted to either qualitative or empirical descriptions. This is primarily due to the large number of interacting factors present in the aqueous papermaking environment as well as variations in furnish properties. Furthermore, the existence of large time constants and recycle flows in the white water system leads to complex mixing dynamics. This inability to quantitatively predict process performance inhibits development of closed-loop control schemes. This thesis is an attempt to bridge the gap between development of fundamental papermaking chemistry models in the laboratory and application of these models in a mill environment.. A dynamic simulation approach is used to model the interactions between chemical additives and furnish particles. Detailed descriptions of the polymer adsorption, flocculation and wire retention and drainage processes are developed. Consistencies of all furnish particles, in particular fines, are faithfully tracked throughout the wet end. The effects of operating variables such as polymer addition rates, furnish composition, degree of stock refining and applied vacuum can be directly assessed in a simulated operating environment. Results are compared against on-line data from a fine paper mill in Canada are shown to be accurate. Identification tools are also developed as part of the overall goal of identifying a model suitable for controller design. A method is first proposed for specifying a confidence interval on the anticipated controller robustness at the identification stage. This is accomplished through optimization of a controller robustness measure with the constraint that the model parameters lie within a (l-⍺)% confidence interval. Parametric nonlinearity is accounted for by this method and the efficacy of the method is shown to be, in part, a function of the degree of this nonlinearity. Input test signals can be chosen which minimize this uncertainty and a method is developed for this purpose. Identification techniques are applied to the High Molecular Weight Anionic Polymer Flowrate White Water Filler Consistency loop. Significant nonlinear behaviour is found to exist in the higher order dynamics of this pairing. While the control relevant identification techniques developed in this thesis are not effective due to the nonlinearities present the value of an accurate dynamic simulation is highlighted.Applied Science, Faculty ofElectrical and Computer Engineering, Department ofGraduat