Design of a fuzzy system for living space thermal-comfort regulation

Dounis, Anastasios I.; Manolakis, D.E.

doi:10.1016/s0306-2619(00)00065-9

Cited by 83 publications

(44 citation statements)

References 13 publications

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“…Then, a set of rules must be defined in order to convert any input linguistic variables combination (whose size depend on the number of controlled variables and actuators) to all possible actuator states. The initial approach for the definition of the rules, and also of the membership functions, was that proposed by Dounis et al [12], then a "trial and error" approach made possible the definition of a set of fuzzy rules relative to every output variable and encoded as a table. Each row in the table represents one rule.…”

Section: Fuzzy Logicmentioning

confidence: 99%

Design and Simulation of a Fuzzy Supervisory Control System Integrated in a Small Public Building

Carbonari¹,

Meschini²,

Benedettelli³

2016

Proceedings of the International Symposium on Automation and Robotics in Construction (IAARC)

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-Public administrations are encouraged to adopt actions for energy requalification of public buildings, which are responsible for considerable amounts of energy consumption. Low-cost technology improvements for energy renovation with high return on investment is a good opportunity when resource shortage hampers the adoption of expensive refurbishment. To this purpose, the integration of advanced control policies may optimize energy use of buildings with minimum hardware enhancement.In this contribution, we evaluated the performances of a control system based on fuzzy logic, supervising local Proportional-IntegrativeDerivative (PID) controllers, through numerical simulation. First, the design process will be described, with particular concern to the proper selection of the rules in the knowledge base and the design of the inference engine. Then, its performances will be compared with the ones provided by the use of just ordinary PID control units. The fuzzy based control system was simulated as an addiction to the heating system of an existing small public building, that is the "San Elpidio a Mare" community clinic located in Italy. The performances were assessed by means of simulations of an energy dynamic model developed in the Dymola TM environment, that had been previously validated with real consumption measurements. In this paper we will show not only what energy saving can be obtained by means of the fuzzy supervisor, but also its satisfactory performances in terms of stability of the control outputs.

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Section: Fuzzy Logicmentioning

confidence: 99%

Design and Simulation of a Fuzzy Supervisory Control System Integrated in a Small Public Building

Carbonari¹,

Meschini²,

Benedettelli³

2016

Proceedings of the International Symposium on Automation and Robotics in Construction (IAARC)

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“…Fuzzy MAS BMS: Fuzzy logic is suitable for BMS because the objective of thermal comfort management may be referred to as the state of mind or psycho-synthesis of the occupants in a building environment that expresses satisfaction with the temperature in the building. This is fundamentally a fuzzy concept, which differs from people to people, and is dependent on the type of activities they are engaged in [18] - [22]. 2.…”

Section: Multi Agent Systemmentioning

confidence: 99%

Intelligent multi-agent system for building heat distribution control with combined gas boilers and ground source heat pump

Mokhtar

Stables

Liu

et al. 2013

Energy and Buildings

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Intelligent energy system refers to the use of intelligent control strategies with the energy system, which can help minimise energy waste and loss, optimise load control, increase and improve energy efficiency and/or maximise the benefits of renewable energy. Renewable energy and intelligent controls are interlinked and correlated with each other. Without intelligent controls, the full benefits of renewable energy technologies may not be achievable, specifically the Ground Source Heat Pump (GSHP) technologies. This was observed, especially by the University of Central Lancashire (UCLan) that had incorporated a GSHP to one of its building. The GSHP is under performing due to the inefficient controls implemented with the GSHP. This paper proposes an intelligent multiagent building management system (MAS BMS) that aims to tackle this issue. Intelligence is provided by an ARTMAP, a type of artificial neural network that provides incremental learning inspired by how human process memory. Simulation results show the proposed intelligent MAS BMS is able to maximise the use of the GSHP effectively by profiling, predicting and coordinating its usage with other energy resources. The proposed method has performed better than the existing control strategies for the GSHP.

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“…The membership function used is the triangular type as shown in Figure 2. This type is simple and give a good controller ISSN: 1693-6930 performance and easy to handle [13], [18]. The important character of these shapes for a purpose of use in fuzzy operation is the fact that they overlap.…”

Section: Fuzzy Logic Controllermentioning

confidence: 99%

“…Yu showed that 67% of the respondents claimed that they intentionally oversized air conditioning design for about 10 to 15% because for future extension, renovation and change of usage [4]. The number of air conditionings in Malaysia has increased significantly from 13 predicted to be about 1,511,276 in 2020 [5]. Hence, it is natural to expect the most energy saving comes from the compressor.…”

Section: Introductionmentioning

confidence: 99%