System identification from small data sets using an output jittering method with application to model estimation of bioethanol production

A novel simple approach is presented for solving small sample size problem in nonlinear dynamic system identification where only a very small number of measured input and output data points are available. The technique is built upon an orthogonal least squares algorithm and a new resampling method called output jittering method,. The proposed algorithm is applied to the model identification of bioethanol production and it shows that a robust and reliable model can be obtained with the new system identification approach.