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An Intelligent Garbage Can Decision-Making Model Evolution Algorithm on Optimal Design of Fuzzy Controller of Intelligent Lighting Systems

In this paper, an intelligent garbage can model-based differential evolution algorithm (IGCMDE) is proposed to simulate human social organization by its population system, based on the differential evolution algorithms (DEs) and the logical framework of the garbage can decision model with group meeting. When faced with issues such as unclear goals and technologies, participators turnover, etc., representatives of all participating parties will communicate, argue, compromise and adapt with each other, in order to find a solution to the problems. Group meetings are conducted to choose the best solution in a more objective, reasonable and efficient way. At last, we used IGCMDE to optimize the fuzzy controller with fuzzy logic control theory. We present a method for daylight blending control with two novel contributions: 1) smart luminance sensing; 2) daylight luminance control. The proposed method was implemented as an intelligent lighting system in a parking tower environment. The result demonstrated that IGCMDE possesses an excellent search performance and the intelligent lighting system showed significant energy savings.