Results are presented from a study of the performance of fizzy, rule-based algorithms for thecontrol of indoor air quality through combined control of natural and forced ventilationstrategies, whilst simultaneously meeting thermal and visual comfort requirements as part of aglobal control strategy aimed at optimizing the indoor environment with minimum energyconsumption. Control algorithms incorporating artificial intelligence techniques offer thepossibility of meeting the required levels of indoor air quality through selective exploitationof the potential for natural ventilation and the use of mechanical ventilation. The controlalgorithms, under development as part of the activities of the BUILTECH research projectfunded in part by DG XU of the European Commission within the framework of the JOULEIII Programme, are founded on the knowledge base of the building physics and support thecontrol of the ventilation, heating, cooling and lighting systems of the building. The C02level has been adopted as the controlled parameter for indoor air quality and is incorporatedwithin the control rules of a fuzzy rule base. The conflicts which arise between the indoor airquality control strategy using natural ventilation and the control of thermal and visual comfortare addressed. The thermal and visual comfort parameters that have been adopted as highlevel petiormance variables are controlled through intelligent compensation and adjustmentof, amongst other factors, the indoor air velocity and solar control devices, with significanteffect on the natural ventilation control strategy.
展开▼
