System identification of activated sludge process

Abstract

In this paper, an activated sludge process model is obtained using two nonlinear system identification techniques. These techniques are Nonlinear ARX Modeling and Hammerstein-Wiener Modeling. A set of raw data from an existing activated sludge process, considered as black box, two different models are obtained and compared in terms of its best fit percentage. From the result, it is concluded that the Hammerstein-Wiener Modeling technique yields better result with lower order and best fit of 91.6%.