  Accounting for more than 40% of global energy consumption, residential and
commercial buildings will be key players in any future green energy systems. To
fully exploit their potential while ensuring occupant comfort, a robust control
scheme is required to handle various uncertainties, such as external weather
and occupant behaviour. However, prominent patterns, especially periodicity,
are widely seen in most sources of uncertainty. This paper incorporates this
correlated structure into the learning model predictive control framework, in
order to learn a global optimal robust control scheme for building operations.
