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An initial design of an advanced control system for an industrial crystallizer train is addressed. The target process is a part of para-xylene production process, and it consists of five scraped surface crystallizers, two centrifugal separators, and two hydrocyclones. An operation policy is derived by solving a constrained nonlinear optimization problem on the basis of a nonlinear process model. Multiloop and multivariable control systems are designed to realize the derived operation policy and their performances are compared through simulation studies. The process is found to be highly interacting and constraint switching is likely to occur under operation condition changes, so that application of constrained multivariable model predictive control may be well justified. The procedures demonstrated in this study will help perform a feasible study for unconventional applications of advanced control technology.

Design of Optimizing Control System for a Multi-stage Industrial Crystallizers Process