Fuzzy logic and intelligent control of engineering systems of buildings

Energy consumption factors in the systems of cooling, heating, air conditioning and lighting in a building have a significant impact on the energy costs. Intelligent energy control methods help modernize the engineering systems of buildings, while using artificial neural networks and fuzzy logic for minimizing energy consumption is especially effective in the operation of buildings. To control energy consumption there was proposed the Mamdani fuzzy inference system, selected membership functions of Gaussian, triangular and trapezoidal shapes in the course of the research, implemented the types and functions of inputs and outputs for engineering systems control subsystems in software. According to the input and output parameters, the following systems were designed: lighting, smart window, HVAC; fuzzy inference tables were built, graphical data analysis was performed. The proposed control solutions for the implementation of fuzzy rules based on linguistic variables make it possible to adapt the building management system to environmental conditions and prevent excessive energy consumption. The study substantiates the choice of energy-consuming parts of the building; when forming control actions, fuzzy logic rules are applied in functional ranges. The fuzzy inference system was shown to generate the solutions in accordance with changing input data, integrated control is implemented, the responses of lighting, heating, ventilation and air conditioning systems are analyzed depending on the input membership function. It is proposed to control the intensity of ambient light using motion sensors, including optical ones. It is shown that the results obtained make it possible to achieve a reduction in lighting energy consumption by 15–25%, maximum use of external light, ensuring a comfortable temperature regime, and also lead to implementing the coordinated and integrated control functions.