A Holistic Approach for the Model-Based Control of Crystal Size, Shape and Purity in Integrated Batch and Continuous Crystallization-Wet Milling Systems

Author Last Name: 
Nagy
Authors: 
Zoltan K. Nagy
Report Type: 
ARR
Publication Year: 
2018
Publication Month: 
12
Country: 
United States

Executive Summary
This report summarizes the main achievements of the second year’s effort of
development of new crystallization technologies for improved crystal size and shape
control during the crystallization process. The successful crystallization process and
system design requires an interdisciplinary effort, which ranges from population balance
model (PBM) development of the system concept, through efficient implementation of
model equations to soft-sensor development, which is required for the model predictive
control (MPC) design as well. This report gives a deeper insight into these
interdisciplinary development efforts, which also highlights the achievable improvements
enabled by the combination of process modeling, high performance process simulation
and optimization.
In the first report we showed that the application of wet-milling during crystallization can
significantly improve the process flexibility and attainable crystal size domain. The GPU
acceleration halved the simulation time, which enabled faster optimization. In this year,
we applied the same principles, but we investigate the effect of milling in addition to
crystal size also on the crystal shape. Since the computational cost associated to
numerically solve the model equations is a power-law function of number of dimensions,
the application of 2D PBMs for this purpose is not feasible without GPU acceleration,
which in this case brought ~1.5 order of magnitude speedup.
The first, full PBM based nonlinear model predictive control (NMPC) was implemented
for the batch crystallization of L-ascorbic acid. The NMPC showed good control
behavior, produced significantly better crystals than the direct nucleation control under
considerably shorter batch time. The novel aspect of this NMPC was that it applied the
fast, approximate CSDCLD transformation, that was presented in the previous report.
The development work of the analogue control system for simultaneous size and shape
control has been started. A major challenge, associated to the calculation time was solved.
Realized deliverables
1. Model development, simulation and preliminary optimization of an integrated batch
crystallizer-wet mill system for bivariate crystal size distribution control
2. Implementation of a full PBM based NMPC for crystal size distribution control
3. Preliminary development work of a real-time feasible full 2D PBM based adaptive
predictive simultaneous crystal size and shape control algorithm