Various critical decision-making and control problems associated with engineering and socio-technical systems are subject to uncertainties. Large-scale data collected from the Internet-of-Things and cyber-physical systems can provide information about the probability distribution of these uncertainties, such as product demand in supermarkets. Such distributional information can be used to dramatically improve the performance of closed-loop systems if they adopt appropriate controllers, which reduce the conservativeness of classical techniques, such as robust control.
