The aim of this line is the development of advanced control techniques that cope with constrained problems, mainly Model Predictive Control (MPC), and that together with the traditional dynamic objectives, take into account additional objectives like managing complex systems, zone control, or economic optimization of large scale processes. This last point copes with important plant objectives like, maximizing the production, reducing costs, controlling prices, etc.
In the last years, the theoretic progress achieved in this line has been remarkable. In particular, control formulations have been proposed, capable of ensuring important properties like stability, recursive feasibility and economic optimality. The drawback of all these formulations is that they can hardly be applied to industrial plants.
The aim of this research line is therefore to re-formulate the theoretical results in literature in such a way they can be easily applied to the industries. That is, designing controllers with low computational burden and simple applicability, taking also into account the theoretic advantages provided by such properties like stability, feasibility, economic optimality, particularly in case of changing economic objectives or operation points.