The sun is the biggest known source of energy in our solar system. We feel its strength when it gets hot during the the day and we notice its absence during the night when we feel cold. So as to be less dependent on the sun as an energy source, we implemented additional heating and cooling sources to maintain the temperature within a comfortable range. The downside to this is that the majority of energy consumed within the housing sector is used up on the heating and cooling alone. To profit from the vast energy source of the sun we propose a user-adaptive and building-adaptive blind control for residential buildings, that is implemented in prefabricated modules for facade renovation. User-adaptive means that it is the occupant who is responsible for the temperature control within the home. Building-adaptive, in this context, means that the temperature control is established automatically without any user input. Through the evaluation of occupant queries we have shown that a general measure for thermal comfort is not possible for all occupants. Consequently, there is a need for a personalized measure of thermal comfort. In order to create this the occupant enters votes via the interface; from this we deduced statistically the probability of comfort relative to the indoor temperature. According to the profile the control sets its target temperature. The profile steadily adapts the user's preferences and through this we can also capture seasonal changes in comfort temperature. This guarantees that at each point in time the control system knows the desired temperature and is taking action to achieve it. The adaption to the building is achieved with the fitting of a simple thermal building model with data collected by the sensors of the control system. We showed that the monitored data sufficiently fits the model. With the help of the simple model we evaluated different control strategies and optimized them according to the thermal profile. For our performance tests we conducted computer simulations as well as a 6-month field study. For the simulations, a specific test bed was suggested that would assess the saving potential, which can then be compared to the performance of the tested control. Results showed that the suggested control system is capitalizing on most of the achievable energy savings and thermal comfort. A 6-month field study in the LESO-PB building was carried out to test the impact on energy demand as well as comfort under real conditions. It appeared that the automatically controlled office needed only approximately 50% of the average heating energy that was used in the manually controlled offices. Furthermore, the probability of thermal comfort was, on average, 10% higher in the automatically controlled offices when compared to those that were controlled manually.