Modelling of Supercritical Fluid Extraction Using Dynamic Genetic Algorithm based Optimisation

Authors:	Yang Simon X., Chongqing Univ. of Posts and Telecommunications, China Zeng Jin, University of Guelph, Canada Wang Guoyin, Chongqing Univ. of Posts and Telecommunications, China
Topic:	1.1 Modelling, Identification & Signal Processing
Session:	Image Processing and Biomedical Applications
Keywords:	Dynamic modelling, Supercritical fluid extraction, Genetic algorithm

Abstract

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.