This paper deals with the application of fuzzy clustering techniques for the model identification of an enhanced FAMIMO biological wastewater treatment process from input-output data. This MIMO system is represented as a set of coupled MISO models of the Takagi-Sugeno type. A comparative study with two clustering algorithms for the construction of the fuzzy model is carried out. The Gustafson-Kessel (GK) algorithm and the so-called robust parallel competitive agglomerative (RPCA) algorithm are considered. From a biotechnological point of view, different simulation experiences were conducted integrating both continuous and batch modes in order to validate the obtained models. Results are reported and discussed