Control of Crystallizers and Dynamic Behaviour

affects the attrition and nucleation kinetics of the process.

• Inappropriate seeding procedures. In batch crystallization processes problems often occur when the amount or size distribution of the seeds crystals or the time of seeding is not optimal. This will result in a final crystal size distribution that is off specification.

• Temperature changes in the crystallizer. This can result in dissolution of the fine crystals in certain zones in the crystallizer, which can have a large impact on the crystallizer dynamics.

• Water injection due to rinse procedures after blockage in product, recycle or circulation lines. This can also result in a temporary decrease in the supersaturation, causing internal dissolution of the fine crystals.

In addition slow, low-order oscillations of the crystal size distribution (CSD) are often observed, which are caused by internal feedback mechanisms in the crystallization process and periodically give rise to an excessive number of fine particles in the product.

To avoid these operational problems, all relevant process variables affecting the crystallization process must be kept within the acceptable limits defined during the design of the process. Not all of the process variables need to be controlled dynamically. Some of them are controlled directly by the equipment design, and others are directly coupled to other variables. Some must be actively controlled to enforce the right process conditions, for instance the temperature profile during a batch cooling process. Others must be manipulated to compensate for the effect of process disturbances. Table 1 shows a list of the major pro-

Table 1 Process variables to be controlled in industrial crystallizers (after Rawlings etal., 1995)

Continuous operation

Batch operation

Process temperature

(Rate of change in) process


Heat flux to/from process

(Rate of change in) heat flux

to/from process

Residence time of crystals

Batch time

Level (volume)

Level (FED batch)(volume)

Feed properties



Flow rate

Impurity level

Slurry concentration

Slurry concentration

Purge flow

Agitator and pump speed

Agitator and pump speed



cess variables for continuous and batch processes. There has been extensive discussion in the literature about the role of each of the process variables and how they are controlled in a variety of crystallizer configurations.

The major process variables in a crystallization process are the level of supersaturation of the solvent, the energy dissipation, the CSD and the distribution of these variables over the crystallizer. These process variables determine to a large extent the kinetic processes (such as nucleation growth and agglomeration) that dominate the crystallization process. They interact with other process variables in a complex way. The presence of interactions and internal feedback mechanisms in the crystallization process limits the success of simple feedback control schemes and favours the use of model-based multivariable controllers, which are able to anticipate these interactions. Unfortunately multivariable control studies for industrial crystallizer are rare and almost completely lack experimental verification.

Depending on the type and scale of the crystal-lizers, the contents will not be uniformly distributed. Profiles are normally present in the temperature, concentration and particle concentrations, especially around heat exchangers and in baffle and boiling zones. It has recently been shown that the presence of such profiles can have a strong impact on the crystal-lizer performance. In general these inhomogenities are acceptable as long as the process variables within these zones stay within the acceptable limits and are time-invariant. The main problem in this respect, however, is that the process models normally used for control design do not take account of the presence of these profiles. Compartmental modelling, which has been used to improve the design of industrial crystallizers, should also be applied to control design.

This article gives an overview of the new developments in the control of the CSD for both continuous and batch crystallizers. Attention is focused on the direct control of the CSD either by simple, single-input/single-output feedback control or by multivariable control, using techniques that have been experimentally verified. The reason for this limitation is that process models normally used in crystallization research have a bad reputation with respect to their prediction of the process behaviour. Different crystal-lizer configurations are analysed with respect to available process actuators. In addition the process models, which form the basis for the controller design and the choice of the measurement technique, are discussed. Some excellent review articles on this topic are used as the starting point of this overview.

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