Identification and Control of a Batch Crystallization Process

Abstract

Crystallization is a slow chemical process evolving in a reactor called crystallizer. A solution initialized in a high temperature is cooled down such that the dissolved solute is transferred from the solution into pure crystalline phase. The evolution of the process characterizes the properties of the crystals in the end-product. The transient nature of the process together with the stochasticity that governs the chemical kinetic phenomena motivate the development of efficient methods for identification and control. The kinetics of the process are modeled with nonlinear equations which contain a number of parameters to be identified from the measured data. An appropriate model is required such that model-based control techniques can be implemented. Under these conditions, experiment design for open loop control of the crystallization is studied in this thesis where a nonlinear model of the crystallization is used as a model structure in the prediction error identification framework. A temperature cooling profile constitutes the input to the system which must be designed in such a way that the crystals formed at the end of the process admit the desired performance criteria. The first part of the thesis deals with the derivation of the optimal cooling profile using the D-optimality criterion in order to obtain the most informative data about the kinetic parameters. Sequentially, an optimization method is used as an open loop control law for the crystallization process. The selection of the optimal input profile is achieved by minimization of the performance degradation, occurring in the controlled process, from the use of the identified model instead of the true unknown system.Delft Center for Systems and ControlMechanical, Maritime and Materials Engineerin