Author Topic: Autonomous Environment Control System using Fuzzy Logic  (Read 1762 times)

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Autonomous Environment Control System using Fuzzy Logic
« on: August 20, 2011, 09:44:36 am »
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Author : Abdul Salam Mubashar, M. Saleem Khan, Khalil Ahmad, Yousaf Saeed
International Journal of Scientific & Engineering Research Volume 2, Issue 6, June-2011
ISSN 2229-5518
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AbstractóThis research work presents an autonomous system for premises environment control using fuzzy logic. This proposed design of control system has four inputs: luminance intensity, luminance mode, temperature and humidity. There are six controlling outputs for luminance controller, air conditioner, ceiling fan, air-cooler fan, water-pump and heating unit. This design model can be applied for indoor and outdoor environments like office, work place, home, commercial areas and streets. This application of fuzzy logic would contribute in minimizing the energy wastages. Fuzzy rules are formulated, applied and tested using MATLAB simulation.
Index Termsó autonomous environment control system, fuzzy logic environment control, luminance intensity, temperature and humidity level control system. 

1   INTRODUCTION                                                                      
THERE are focused considerations for controlling en-vironment suitable to its living beings for not only easi-ness but also providing comfort to increase working capacities with fresh mind. It would save and enhance energy resources also. There have been criticalities for limitations of energy resources including ever increasing requirements for energy utilizations. There are wastages of energy during its utilizations even in needlessness specifically in deregulated environments [1]. It can be overcome through proper scheduling but it involves hazards. An appropriate solution is to make autonomous and controlled systems according to the requirements. The proposed system is based on fuzzy logic. Fuzzy Logic is suitable for uncertainties issues. The non-probabilistic problems are dealt with fuzzy logic [3]. There are different fuzzy inference system and defuzzification techniques were reported [2], [6]. However this research provides comprehensive application of fuzzy Logic for the particular appliances together involving the automation of light controller, air conditioner, heating unit ceiling fan and air-water-cooler controlling luminance, temperature and humidity. It would also save the energy cost. The feelings of temperature vary with the different levels of humidity. Humidity is the amount of water vapor in the air. In high humidity living beings feel the atmosphere very hot in summer because it reduces the effectiveness of sweating to cool the body by reducing the evaporation of perspiration from the skin. At normal temperature with wet atmosphere, it would be felt cool by living beings because water vapors absorb energy rapidly [5]. Air-cooler appliance works on this phe-nomenon. It includes air-cooler fan and water pump. It is something like window fan [7]. The phenomenon is also implemented for other appliances to save energies. By decreasing or increasing humidity there is less energy required for controlling temperature and making appropriate luminance according to the specifications to minimize energy wastages and discomfort. The frame work of this paper comprises, design and structure of the proposed autonomous environment control system in section 2, section 3 gives the design algorithm of autonomous environment control system, section 4 describes simulation results and discussion whereas Section 5 gives conclusion and future work.

2   DESIGN AND STRUCTURE OF THE PROPOSED AUTONOMOUS ENVIRONMENT CONTROL SYSTEM
There are included Fuzzyfier, Inference Kernel connected with Knowledgebase and Defuzzifier in the proposed fuzzy logic system. The Knowledgebase contains Database, Rule base and Membership Functions.
   The fuzzifier converts the Crisp values into Linguistics values. The linguistics values are manipulated for inference engine [4]. The kernel of the system provides the output according to the Rule Selector. The Rule Selector selects rules according to the Knowledgebase. Knowledgebase comprises of Database, Rule base and Membership Functions [3]. Rule base is built up carefully considering all possible effective situations. There have been incorporated four input variables: Luminance Intensity, Luminance Mode, Temperature and Humidity. There are six outputs controlling appliances: Luminance Controller, Air Conditioner, Ceiling Fan, Air-Cooler Fan, Water Pump and Heating Unit. There have been considered sixty rules for the effective situations focusing energy saving. There are used sixty operators for the rule se-lector. Luminance mode can be set according to the re-quirement. However there are proposed Time Oriented Luminance Intensity Mode Specifications for three types of premises including indoor and outdoor environ-ments.
The feelings of hotness depend upon temperature and humidity. During low temperatures, the heating systems work for long enough to convert the climate into dry resulting discomfort. At normal temperature heating system remains off while there wet climate effects cool.

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