SINCPRO: Self-learning Model for INtelligent Predictive Control System for Crystallization PROcess

  • A tool for the rigorous and hybrid modeling of crystallization processes that can be used (a) for parameter estimation (b) for optimization of design and operation (c) starting point for model-based control applications;
  • An observer/feedback system based on hybrid models made of a rigorous mechanistic model and an empirical model (e.g. Extended Kalman filter; horizon approach, self- learning, intelligent (learning) operating system);
  • A control toolbox consisting of a Model Predictive Control applicable to a wide range of crystallization processes.

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Project Summary – SINCPRO