GAUSSIAN PROCESS MODELLING CASE STUDY WITH MULTIPLE OUTPUTS
Juš Kocijan, Alexandra Grancharova · 2010
The Gaussian-process (GP) model is an example of a probabilistic, nonparametric model with uncertainty predictions. It can be used for the modelling of complex nonlinear systems and also for dynamic systems identification. The output of the GP model is a normal distribution, expressed in terms of the mean and variance. At present it is applied mostly for the modelling of dynamic systems with one output. A possible channel structure for multiple-input multiple-output model and a case study for the modelling of a system with more than one output, namely a gas-liquid separator, is given in this paper.