Non-linear tracking of glass transition temperatures for free radical emulsion copolymers

Abstract A new method for the control and estimation of the glass transition temperature ( T G ) of free-radical copolymers is presented, and is intended to improve the on-line control of the quality of these products. As an example of this approach, a non-linear control law is used to manipulate the monomer feed flow rate of semi-batch copolymerisation in emulsion in order to pursue a predefined trajectory of T G . The measured output required for an effective closed-loop system is provided through calorimetric measurements of the overall monomer conversion, and both the number of moles of monomer and the total number of radicals in the polymer particles are estimated using non-linear observation techniques. The global approach is based on a simplified kinetic model of the emulsion copolymerisation of water-insoluble monomers, which was validated through laboratory scale experiments. In addition to the overall and partial conversions, the model also predicts the time variations of the instantaneous copolymer composition and T G and of the average particle size. The state and parameter observer was evaluated with both simulated and real polymerisation data, and is shown to perform very well. The tracking ability of the non-linear control strategy was found to be robust and accurate despite uncertainty and noise in both the simulated model and experimental measurements.

[1]  F. Schork,et al.  On-Line Monitoring of Emulsion Polymerization Reactor Dynamics , 1981 .

[2]  J. Gauthier,et al.  A simple observer for nonlinear systems applications to bioreactors , 1992 .

[3]  Hans Schuler,et al.  Calorimetric-state estimators for chemical reactor diagnosis and control: review of methods and applications , 1992 .

[4]  P. Canu,et al.  Composition control in emulsion copolymerization. I. Optimal monomer feed policies , 1994 .

[5]  M. Morbidelli,et al.  Densimetry for on‐line conversion monitoring in emulsion homo‐ and copolymerization , 1993 .

[6]  Costas Kiparissides,et al.  On‐line monitoring of polymer quality in a batch polymerization reactor , 1986 .

[7]  John F. MacGregor,et al.  On-line Reactor Energy Balances via Kalman Filtering , 1987 .

[8]  Alain Guyot,et al.  Controlled Composition in Emulsion Copolymerization Application to Butadiene-Acrylonitrile Copolymers , 1984 .

[9]  J. Macgregor,et al.  State estimation for continuous emulsion polymerization , 1991 .

[10]  Timothy F. L. McKenna,et al.  Joint use of calorimetry, densimetry and mathematical modelling for multiple component polymerizations , 1996 .

[11]  Alexander Penlidis,et al.  ON-LINE SENSORS FOR POLYMERIZATION REACTORS , 1990 .

[12]  Mondher Farza,et al.  A nonlinear approach for the on-line estimation of the kinetic rates in bioreactors , 1997 .

[13]  E. Sudoł,et al.  Details of the emulsion polymerization of styrene using a reaction calorimeter , 1996 .

[14]  Harold A. S. Schoonbrood,et al.  Copolymer composition control by means of semicontinuous emulsion copolymerization , 1992 .

[15]  H. Schuler,et al.  Real-time estimation of the chain length distribution in a polymerization reactor—II. comparison of estimated and measured distribution functions , 1986 .

[16]  Andrew Klein,et al.  An experimental study of adaptive Kalman filtering in emulsion copolymerization , 1991 .

[17]  C. Kiparissides.  Polymerization reactor modeling: A review of recent developments and future directions , 1996 .

[18]  Klavs F. Jensen,et al.  Estimation of the molecular weight distribution in batch polymerization , 1988 .

[19]  John F. MacGregor,et al.  Feedback control of polymer quality in semi-batch copolymerization reactors , 1992 .

[20]  N. Johnston.  Sequence Distribution-Glass Transition Effects. III. α-Methylstyrene-Acrylonitrile Copolymers , 1973 .

[21]  Zhang Suzhen,et al.  Real-time estimation of the chain length distribution in a polymerization reactor , 1985 .

[22]  J. Macgregor,et al.  On‐line inference of polymer properties in an industrial polyethylene reactor , 1991 .

[23]  Klavs F. Jensen,et al.  On‐line molecular weight distribution estimation and control in batch polymerization , 1994 .

[24]  Gilles Fevotte,et al.  An adaptive inferential measurement strategy for on-line monitoring of conversion in polymerization processes , 1996 .