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 delta-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 delta - endotoxins of the \emph{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.