Modelling and Adaptive Control of a Batch Evaporative Crystalliser

摘要

This paper describes algorithms for the modelling and adaptive control of a sugar crystallisation unit. The feed flow rate of sugar liquor or syrup and the vacuum pressure have been selected as input control variables. The aim is to force the operation into following optimal profiles of brix and temperature. The state vector in the dynamic model includes temperature, dissolved sucrose and dissolved impurities in liquor, mass of sucrose crystals and the moments of order zero to five in the characterisation of crystal size distribution. Main intensive variables such as brix, supersaturation, crystal content and masscuite consistency are calculated from the set of state variables. The control design is based on a simple low order linear discrete model with unknown and possibly time-varying parameters. The parameters of this model are estimated using least squares algorithm taking into account the requirements for long-term adaptive control. The dynamic model gives an accurate representation of the industrial behaviour of this batch crystalliser. The Generalised Predictive Control (GPC) which is based on the minimisation of a receding horizon cost function, is used for feedback control. Several simulation studies highlight the applicability of the involved adaptive control algorithm. Control simulations show an improved performance of the proposed control algorithm over classical alternatives (PID), hence suggesting its industrial implementation.