This research topic develops methods for advanced control and process optimization including industrial applications. In particular:
- Methods for nonlinear model predictive control, oriented to complex dynamics, with applications in industrial systems.
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- Optimization of the operation of large-scale processes, oriented to the improvement of performance indexes, usually of economic nature, taking into account operation and process constraints, with applications such as the optimal management of hydrogen networks, natural gas networks or evaporation and heat-recovery sections.
- Integration of discontinuous and continuous processes, mixing real time scheduling of the operation with the optimal control of process units, with applications in sugar factories, cleaning scheduling of heat exchangers in fibers factories, or production scheduling in the sterilization of canned food.
- Integration of online control with other enterprise decision and optimization layers, oriented to the global operation, with applications in refineries and food processing facilities.
- Methods for control and optimization under uncertainty, hybrid and distributed, that take into account uncertainty in the models and process variables, and the presence of discrete decisions, accounting for the need of selecting alternatives between various agents or equipments.
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