|Thesis abstract: |
The aim of this research is to develop model predictive control (MPC) strategies for stochastic systems based on randomized methods, such as the scenario approach. The control is designed so as to explicitly take into account the presence of uncertainty and achieve a desired level of performance and robustness. The method is developed with reference to an air traffic control application, where new efficient methods to manage air space are investigated. The focus will be on the uncertain dynamics of the aircraft and on the constraints that arise when air traffic is increased.