A rule-based fuzzy logic control system for HVAC processes : VRV system for a multi-storey residential flat

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A rule-based fuzzy logic control system for HVAC processes : VRV system for a multi-storey residential flat


Author: Chan, King-yeung
Title: A rule-based fuzzy logic control system for HVAC processes : VRV system for a multi-storey residential flat
Degree: M.Sc.
Year: 1997
Subject: Buildings -- Energy conservation
Heat pumps
Air conditioning
Fuzzy logic
Hong Kong Polytechnic University -- Dissertations
Department: Multi-disciplinary Studies
Pages: ix, 88, [45] leaves : ill. ; 30 cm
Language: English
InnoPac Record: http://library.polyu.edu.hk/record=b1398617
URI: http://theses.lib.polyu.edu.hk/handle/200/4844
Abstract: Heating, ventilating and air conditioning processes maintain environmental conditions for human comfort and some products or processes within the building but consume a great deal of energy. Extensive research and development on energy conservation in buildings have become the main concern for scientists since the oil crisis in 1973. This dissertation summaries different energy saving control methods for heat pumps with variable refrigerant volume system. Vagueness does not have sharp morphology but is very common in human thought processes. The cognitive information is characterized by using relative grades for human intention. The fuzzy logic concept is intended to emulate some of the cognitive functions of human beings in a machine in order to generalize the definition of information. This concept is applied to the heat pump with variable refrigerant volume system for room temperature control. A fuzzy logic control system for room temperature control has been developed. This system makes decisions for individual and integral control according to the different indoor temperature conditions. The refrigerant flow volume is regulated by the compressor speed which is under the control of the fuzzy logic controller. The fuzzy logic controller consists of a fuzzifier, a knowledge base for fuzzy rules, a fuzzy logic inference operator and a defuzzifier. The fuzzifier provides not only a fuzzification action which makes a crisp quantity becomes fuzzy but also a way for developing membership function as well. The data base for fuzzy rules gathers all the rules in respect of the human knowledge and represents the knowledge of control. The fuzzy logic inference operator comprises the outer envelop of the individual truncated membership forms from each rules. The defuzzifier deduces a fuzzy set from the aggregated form to a crisp single valued quantity which produces an overall control action. A set of knowledge matrices governed by fuzzy control rules have been built up to represent the room temperature control knowledge for a prototype two storeyed residential flat. This method enables the representation of a large amount of knowledge in a few matrices and makes fuzzy logic control feasible for a complex process. In the evaluation test of the fuzzy logic controller, the results have shown that the compressor speed could be successfully controlled and regulated from 5% to 93% of its speed subject to the different room conditions.

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