Application of on-line calorimetry to the advanced control of batch crystallizers

Abstract

For batch crystallizers cooled through vacuum, the advanced tracking of temperature trajectories, which involves severe non-linear and non-stationary features, is somewhat difficult to achieve. A generalized predictive control law has been applied to a bench-scale plant and, for the sake of control robustness and process safety, an adaptive supervisor was designed. A major problem in unseeded batch crystallizers being to detect the nucleation, an estimate of the crystallization heat flow is computed through on-line calorimetry by using a recursive least-squares identification algorithm. So, relevant real-time information is provided which is successfully applied to monitor the setpoint pressure of the evaporative crystallizer. Besides process control, it is shown that calorimetric estimates are of great interest in real-time batch crystallization analysis and diagnosis.