Internal model control based on a Gaussian process prior model

To improve transparency and reduce the curse of dimensionality of non-linear black-box models, the local modelling approach was proposed. Poor transient response of local model networks led to the use of non-parametrical probabilistic models such as the Gaussian process prior approach. Recently, Gaussian process models were applied for minimum variance model for non-linear internal model control. The invertibility of the Gaussian process model is discussed and the use of predicted variance is illustrated on a simulated example.