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S. De, B. J. Mauricio, J. C. Pinto and E. L. Lima, “Control of a Chaotic Polymerization Reactor: A Neural Network Based Model Predictive Approach,” Polymer Engineering & Science, Vol. 36, No. 4, 1996, pp. 448-457. doi:10.1002/pen.10431

has been cited by the following article:

• TITLE: Nonlinear Multiple Model Predictive Control of Solution Polymerization of Methyl Methacrylate

  AUTHORS: Masoud Abbaszadeh

  KEYWORDS: Model Predictive Control, Methyl Methacrylate, Nonlinear Multiple Model Control, Polymerization

  JOURNAL NAME: Intelligent Control and Automation, Vol.2 No.3, August 8, 2011

  ABSTRACT: A sequential linearized model based predictive controller is designed using the DMC algorithm to control the temperature of a batch MMA polymerization process. Using the mechanistic model of the polymerization, a parametric transfer function is derived to relate the reactor temperature to the power of the heaters. Then, a multiple model predictive control approach is taken in to track a desired temperature trajectory.The coefficients of the multiple transfer functions are calculated along the selected temperature trajectory by sequential linearization and the model is validated experimentally. The controller performance is studied on a small scale batch reactor.