Intelligent control system for reconciliation of the energy savings with comfort in buildings using soft computing techniques

In this paper, we present a novel intelligent coordinator control system based on hierarchical structure. The presented structure consists of one coordinator and five fuzzy logic controllers. The intelligent coordinator architecture contains uses a master and a slave agent. The master agent is an economy behavior fuzzy system and the slave agent consists of two fuzzy negotiation machines (FNMs) and one decision logic unit. Type-1 FS models are chosen to characterize the concepts of thermal comfort, illuminance and carbon dioxide concentration. The word “comfort” is represented by a 3D fuzzy set in fuzzy cube. Using the symmetric fuzzy equality measure we can measure the membership grade of the 3D fuzzy comfort set. We present the structure of a fuzzy controller-agent (FCA) and propose the tuning of parameters of the FLC by genetic algorithms (GAs). The simulation results show that the proposed intelligent control system successfully manages the users’ preferences for thermal and illuminance comfort, indoor air quality and the energy conservation.