期刊
ENERGY AND BUILDINGS
卷 33, 期 6, 页码 545-551出版社
ELSEVIER SCIENCE SA
DOI: 10.1016/S0378-7788(00)00097-9
关键词
artificial intelligence; fuzzy logic; non-linear control; thermal comfort
Fuzzy models and controllers are represented by if-then rules and thus can provide a user-friendly and understandable representation of combined quantitative and qualitative description. The qualitative rules result in a quantitative non-linear controller well-suited for nonlinear systems that controls thermal comfort with vague defined objectives. The fuzzy models are achieved through experimental identification by varying the inputs so that the fan-coil reaches the states encountered in normal operation. These models may be used for control or for simulation. On its domain of validity, the fuzzy controller behaves better then a classical controller. In fact, the main advantage of fuzzy controller is the easiness of introducing operating modes and poor defined objectives. (C) 2001 Elsevier Science B.V. All rights reserved.
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