Many engineering systems can be characterised as complex since they have a nonlinear behaviour incorporating a stochastic uncertainty. Urban traffic systems or traffic pollution propagation models are typical representatives of such complex systems. One of the most appropriate methods for modelling such systems is based on the application of Gaussian processes.

The project is aimed at investigating qualitative properties of stochastic infinite dimensional systems (in particular, stochastic partial differential equations) and at research in infinite dimensional stochastic control theory. More specifically, the following topics will be emphasized: 1.

The project aims to develop a novel on-line estimator of the key process variable in rolling mills by mixing multiple models with different sensitivities to inaccuracy in process data. The approach relies on the systematic treatment of uncertainty and merging of all available information.