Fuzzy Modelling for Distillation Column

R. Yusof, M. Khalid, and M.F. Ibrahim (Malaysia)


Fuzzy model, genetic algorithms, distillation column.


Fuzzy system's ability of extracting information from measured data has been exploited for identification of nonlinear and complex system. Takagi-Sugeno (TS) Fuzzy system is one of the most useful structures for multi input multi output (MIMO) dynamical system modelling. This paper presents a hybrid method to tune the parameters of TS fuzzy system automatically using Genetic Algorithms (GA) and Recursive Least Square (RLS) technique. The effectiveness of this approach is illustrated by the identification of temperature profile of batch distillation column. The results show that the proposed system gives a more accurate model than the conventional TS fuzzy model and linear model.

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