Fuzzy clustering based models applied to petroleum processes
Miguel Angel Ramírez Canelón, Eliezer Colina-Morles · 2008
The application of fuzzy clustering techniques has recently become in a very useful alternative in the area of modeling and identification of complex industrial processes. In particular, fuzzy clustering techniques such as Fuzzy C-Means and the Gustafson-Kessel (GK) algorithms will be analyzed and applied in details in this paper. These algorithms will be implemented in the construction of Takagi-Sugeno fuzzy models for the gas-liquid separation process, the water-oil separation process and the oil-heating process, which are important processes in the oil industry. Validations of the obtained fuzzy models will be performed and some conclusions will be established.