Adaptive MIMO neuro-fuzzy logic control of a seeded and an unseeded anti-solvent semi-batch crystallizer

Department of Chemical and Biochemical Engineering, The University of Western Ontario, London, Ont., Canada N6A 5B9
Chemical Engineering Science 01/2008; DOI: 10.1016/j.ces.2007.07.022

ABSTRACT This study explores the implementation of a two input/two output adaptive neuro-fuzzy logic controller on an anti-solvent semi-batch crystallization process. The solution concentration and the solubility curve of paracetamol (PA) in a mixture of water and isopropanol in the range of temperatures between 10 and were determined using attenuated total reflection (ATR)-Fourier transform infrared (FTIR) spectroscopy. The in situ chord length distribution of crystals was obtained from laser backscattering by focus beam reflectance measurement (FBRM) probe. The controlled variables were the supersaturation and the difference in the chord length counts between two sampling times, and the manipulated variables were the cooling rate and anti-solvent flow rate. The ‘direct’ objectives of this study were to keep the controlled variables inside their predetermined ranges. The ‘indirect’ objectives were to improve the end-of-batch properties that included batch time, yield, and particle size distribution. Performance of the adaptive neuro-fuzzy logic controller for the closed-loop system was evaluated based on meeting the ‘direct’ and ‘indirect’ objectives. The best results in terms of batch time and product yield for unseeded experiments were 280 min and 95%, respectively. However, the most significant improvement was noted in the seeded set of experiments that resulted in 225 min batch time, an increase of the volume weighted mean size by , and 99% product yield.

  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: The paper presents a novel control approach for crystallization processes, which can be used for designing the shape of the crystal size distribution to robustly achieve desired product properties. The approach is based on a robust optimal control scheme, which takes parametric uncertainties into account to provide decreased batch-to-batch variability of the shape of the crystal size distribution. Both open-loop and closed-loop robust control schemes are evaluated. The open-loop approach is based on a robust end-point nonlinear model predictive control (NMPC) scheme which is implemented in a hierarchical structure. On the lower level a supersaturation control approach is used that drives the system in the phase diagram according to a concentration versus temperature trajectory. On the higher level a robust model-based optimization algorithm adapts the setpoint of the supersaturation controller to counteract the effects of changing operating conditions. The process is modelled using the population balance equation (PBE), which is solved using a novel efficient approach that combines the quadrature method of moment (QMOM) and method of characteristics (MOC). The proposed robust model based control approach is corroborated for the case of various desired shapes of the target distribution.
    Computers & Chemical Engineering. 01/2009;
  • [Show abstract] [Hide abstract]
    ABSTRACT: This article presents an experimental study of simultaneous optimization with respect to two variables (cooling rate and flow-rate of antisolvent) in an offline and online (real-time) manner on a semibatch crystallizer. The nucleation and growth kinetic parameters of paracetamol in an isopropanol-water cooling, antisolvent batch crystallizer were estimated by nonlinear regression in terms of the moments of the crystal population density. Moments of crystal population were estimated from the measured chord length distribution, generated by the FBRM®, and the supersaturation was calculated from the measured concentration by attenuated total reflectance-fourier transform infrared spectroscopy. The results of real-time optimization showed a substantial improvement of the end of batch properties (the volume-weighted mean size and yield). For the same objective function, the real-time optimization method resulted in an increase in the volume-weighted mean size by ∼100 μm and 15% of theoretical yield compared with the best result obtained in an offline optimization manner. © 2009 American Institute of Chemical Engineers AIChE J, 2009
    AIChE Journal 07/2009; 55(10):2591 - 2602. · 2.49 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: The metastable zone width (MSZW), induction time and primary nucleation kinetics have been measured and estimated for simultaneous anti-solvent and cooling crystallization of paracetamol in iso-propanol/water solution. ATR-FTIR spectroscopy and laser back-scattering are used to measure the solute concentration and primary nucleation event, respectively. Response surface analysis was applied to find the contribution of the crystallization mechanism on the MSZW and obtain a statistical model for quick estimation of the MSZW. Two theoretical approaches for the estimation of nucleation rate kinetic parameters from experimental data are presented. The methods are obtained by modifying the classical Nyvlt's correlation for simultaneous cooling/anti-solvent crystallizations. The nucleation order n for primary nucleation was deduced from the slope of a linear plot of log(MSZW) vs. log(cooling and anti-solvent rates). The induction time was also estimated by changing the classical methods for combined cooling and anti-solvent crystallization.
    Journal of Crystal Growth 01/2009; 311(14):3640-3650. · 1.55 Impact Factor