Modelling of Supercritical Fluid Extraction Using Dynamic Genetic Algorithm Based Optimisation

نویسندگان

  • Simon X. Yang
  • Jin Zeng
  • Guoyin Wang
چکیده

In food and chemical industry, supercritical fluid extraction is an environmental-friendly separation technique, which plays an important role in biomaterial processing. In this paper, a dynamic optimisation model for supercritical fluid extraction is proposed by combining a transformation based genetic algorithm and the Peng-Robinson equation of state. The proposed dynamic model for the relationship between pressure and yield of biomaterial can recognise the change of temperature, and is able to adapt to a new solution by finding a near-optimal k12 parameter without restarting the system as other models. The effectiveness of the proposed approaches is demonstrated by simulation and comparison studies. Copyright c ©2005 IFAC.

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تاریخ انتشار 2005