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Rules forfuzzy models are automatically generated using data from CFD simulations. The HVAC controlpresented here estimates the averaged temperature of an occupied zone based on the temperatureof the sensor location using a fuzzy model, and conducts PID control so that the estimatedtemperature becomes the set temperature. From the results of control simulation using CFD, thisHVAC control based on a fuzzy model is able to achieve control with little offset as comparedwith conventional PID control where the temperature at the sensor location is the representativetemperature of the occupied zone. This paper is comprised of six chapters, and a short summaryof each chapter is given below.Chapter 1 consists of the background behind this study and an abstract of the methodproposed in this study.Chapter 2 describes fuzzy modeling and CFD, which are elemental technologies in thisstudy, and also explains the control method (FM-PID) based on the fuzzy model.Chapter 3 presents a case study using CFD simulation based on 9 cases―consisting of 3different usage purpose and 3 sensor positions―as parameters. In this chapter, a comparison ismade between FM-PID control in a CAV (constant air volume) system and PID control, wherethe sensor temperature serves as the representative temperature. 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多目的大空間におけるファジィモデルを用いた空調制御に関する研究
https://uec.repo.nii.ac.jp/records/1148
https://uec.repo.nii.ac.jp/records/114808a72bf2-dfff-4949-b747-7873f84d651c
名前 / ファイル | ライセンス | アクション |
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9000000351.pdf (8.4 MB)
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Item type | 学位論文 / Thesis or Dissertation(1) | |||||
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公開日 | 2009-03-24 | |||||
タイトル | ||||||
言語 | ja | |||||
タイトル | 多目的大空間におけるファジィモデルを用いた空調制御に関する研究 | |||||
タイトル | ||||||
言語 | en | |||||
タイトル | A Study on HVAC Control Based on a Fuzzy Model for Multipurpose Large Indoor Spaces | |||||
言語 | ||||||
言語 | jpn | |||||
資源タイプ | ||||||
資源タイプ識別子 | http://purl.org/coar/resource_type/c_46ec | |||||
資源タイプ | thesis | |||||
著者 |
植田, 俊克
× 植田, 俊克 |
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抄録 | ||||||
内容記述タイプ | Abstract | |||||
内容記述 | In large indoor spaces, air volume is large, and there is great distance between the occupiedzones and air outlets as well. As a result, it is easy for time delays and instabilities to arisewith HVAC (Heating, Ventilating and Air-conditioning) systems for large spaces. In addition,large spaces such as dome type baseball stadiums and event halls are used for a variety ofpurposes, and there are limitations on the locations where the sensors for an HVAC controlsystem can be installed. As a result, it is difficult to obtain representative temperature and airvelocity distributions of occupied zones. This paper proposes an HVAC control system using afuzzy model as a method to resolve these problems. A fuzzy model is constructed by using dataobtained from estimating various parameters such as outlet air temperature, outlet air volume,and human body load, which affect the temperature distribution within a space, by using CFD(Computational Fluid Dynamics) simulations. Fuzzy models adopt a simplified fuzzy reasoningmethod, and can estimate nonlinear temperature characteristics with high accuracy. Rules forfuzzy models are automatically generated using data from CFD simulations. The HVAC controlpresented here estimates the averaged temperature of an occupied zone based on the temperatureof the sensor location using a fuzzy model, and conducts PID control so that the estimatedtemperature becomes the set temperature. From the results of control simulation using CFD, thisHVAC control based on a fuzzy model is able to achieve control with little offset as comparedwith conventional PID control where the temperature at the sensor location is the representativetemperature of the occupied zone. This paper is comprised of six chapters, and a short summaryof each chapter is given below.Chapter 1 consists of the background behind this study and an abstract of the methodproposed in this study.Chapter 2 describes fuzzy modeling and CFD, which are elemental technologies in thisstudy, and also explains the control method (FM-PID) based on the fuzzy model.Chapter 3 presents a case study using CFD simulation based on 9 cases―consisting of 3different usage purpose and 3 sensor positions―as parameters. In this chapter, a comparison ismade between FM-PID control in a CAV (constant air volume) system and PID control, wherethe sensor temperature serves as the representative temperature. Based on the results of thiscomparison, it was demonstrated that with FM-PID control, it is possible for the temperature inan occupied zone to serve as the set temperature without depending on the usage purpose orsensor location.Chapter 4 presents a case study similar to the one in Chapter 3, and also reviews controlperformance in a VAV (variable air volume) system. A VAV system is superior in energyconservation as compared to the CAV system, and is used widely in offices, etc. However,since temperature distribution changes greatly when the VAV system is used in large, indoorspaces, there are very few examples of the VAV system being used in such spaces. Based onthe results of control simulation using CFD, it was demonstrated that FM-PID control can besuitable for VAV systems in large, indoor spaces.Chapter 5 introduces a control simulation with the VAV system that takes the introductionof outside air into consideration, which demonstrates the high control performance and energyconservation effects of FM-PID control.Chapter 6 consists of the results of this study as well as future issues for research. | |||||
学位名 | ||||||
学位名 | 博士(工学) | |||||
学位授与機関 | ||||||
学位授与機関名 | 電気通信大学 | |||||
学位授与年度 | ||||||
内容記述タイプ | Other | |||||
内容記述 | 2008 | |||||
学位授与年月日 | ||||||
学位授与年月日 | 2009-03-24 |