Nonlinear inferential multi-rate control of Kappa number at multiple locations in a continuous pulp digester

Abstract

The continuous pulp digester represents a large-scale, distributed parameter system. Control of the spatial profile of degree of cooking, characterized by the Kappa number, rather than its endpoint value can effectively control properties that are dependent on the history of cooking. However, profile control of such large-scale distributed parameter systems throws up new challenges in estimation and control. We design a nonlinear model predictive controller using a multi-rate extended Kalman filter to infer and control discrete points along the Kappa number profile. Both, the plant and controller models are based on first principles. The design is tested for significant mismatches in parameters, initial state errors, and stochastic disturbances in the entering wood composition.