Prediction of the Syngas composition of a gasification process

The scope of this work is the development of a mathematical model of a gasification process to be used for the prediction of the Syngas composition. The predictions are intended to support the gascromathographic measurements of the Syngas composition which are often not available due to periodic calibrations. This work represents the first step of broader project which scope is the development of a supervisory controller to perform process optimization and fault detection and isolation. The original contribution of the paper is the design of a new procedure for the selection of the dataset used to design and to identify the model; the approach is based on the use of the Fuzzy C-means (FCM) algorithm for the generation of the main clusters used as input data in the identification process. The presented results show the goodness of the proposed FCM method in filtering a large dataset and the reliability of the identified model in the prediction of the Syngas composition.