In this paper a novel optimal Model Reference Adaptive Control approach, developed to tame the thermohygrometric behaviour of buildings as well as to guarantee the indoor comfort, is presented. The main advantages of the proposed method are: (i) no-need of a priori knowledge of the specific building dynamics due to climate, occupants' behaviour, building use, envelope features and utility rates; (ii) robustness with respect to a large class of perturbations, external disturbances, nonlinear unmodelled dynamics or parameters uncertainty; (iii) ability to impose desired optimal dynamics; (iv) accurate regulation and fast tracking of indoor air temperature and humidity in the case of stringent requirements in special building spaces (e.g. hospitals, museums, laboratories, etc.). In order to investigate the effectiveness of the proposed method, the developed strategy has been implemented in the new release of a white-modelling building energy performance simulation code, called DETECt 2.3. The tool enables multi-zone building simulation analyses and is capable to dynamically predict: (i) spaces sensible and latent heating and cooling demands and loads; (ii) indoor air temperatures and humidity, as well as building envelope internal and external temperatures; (iii) the performance of phase change materials (PCM) embedded in building enclosures and for any layer configuration; (iv) the thermohygrometric comfort of occupants. In order to analyse the effectiveness and robustness of the proposed control strategy, several case studies have been carried out. They refer to some reference buildings with different geometry, use and construction materials (also including PCM integrated into the building envelope) simulated in different weather conditions. For each case study, both continuous and intermittent control system regimes have been considered. Results confirm the ability of the developed approach to achieve the selected indoor air temperature and humidity conditions in order to guarantee indoor comfort in uncertain conditions. The numerical analysis is complemented with the rigorous analytical proof of asymptotic stability. (C) 2015 Elsevier Ltd. All rights reserved.