Comparison on the estimation of the biomass of a batch bioreactor through fuzzy systems, neural networks and adaptive neuro-fuzzy inference system

The estimation of biomass production of d-endotoxins of the Bacillus thuringiensis (Bt) is a major problem in biotechnological processes, as bio-insecticides, which has been addressed with different methodologies such as extended Kalman filters (EKF), phenomenological observers, among others. This paper presents a comparison in the estimation of biomass concentration of d - endotoxins of the Bacillus thuringiensis (Bt), using Mamdani fuzzy inference systems (FIS), neural networks (NN) and adaptive neuro-fuzzy inference system (ANFIS) trained with differents clustering algorithms; and comparing the associated outcomes among these. © 2011 IEEE