Salah-ud-din Khokhar, Yasir Noor, Qinke Peng, Umair Khokhar, A. Asif, Nabeel K. Abid
{"title":"低成本节能的模糊厨房通风控制系统","authors":"Salah-ud-din Khokhar, Yasir Noor, Qinke Peng, Umair Khokhar, A. Asif, Nabeel K. Abid","doi":"10.1109/ICRAI47710.2019.8967397","DOIUrl":null,"url":null,"abstract":"In this paper, a kitchen ventilation control system is modeled using fuzzy system-modeling technique and implemented through a microcontroller. Based on the Mamdani’s model, the designed fuzzy kitchen ventilation system accepts four crisp input values from Stove Heating, Cooking Fumes, Humidity, and Temperature sensors; divides the treatise into sections, each with two fuzzy variables; fire rules and assigns singleton values to each output variable. A single defuzzifier is deployed to adjust the speed of actuator: the kitchen exhaust fan. The model is implemented and verified using a microcontroller by utilizing its pulse-width modulation (PWM) capabilities. Comparative analysis of the results confirms the high accuracy of the proposed model which yields a maximum relative error of ~ 1 % between the model designed outputs and corresponding measured duty cycles of output pulses generated by the microcontroller. The rotations per minute (RPM) of 12 V dc fan, however, show a maximum relative error up to ~ 8 % due to its intrinsic non-linear behavior with respect to the duty cycle of input pulses.","PeriodicalId":429384,"journal":{"name":"2019 International Conference on Robotics and Automation in Industry (ICRAI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Low Cost and Energy Efficient Fuzzy based Kitchen Ventilation Control System\",\"authors\":\"Salah-ud-din Khokhar, Yasir Noor, Qinke Peng, Umair Khokhar, A. Asif, Nabeel K. Abid\",\"doi\":\"10.1109/ICRAI47710.2019.8967397\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, a kitchen ventilation control system is modeled using fuzzy system-modeling technique and implemented through a microcontroller. Based on the Mamdani’s model, the designed fuzzy kitchen ventilation system accepts four crisp input values from Stove Heating, Cooking Fumes, Humidity, and Temperature sensors; divides the treatise into sections, each with two fuzzy variables; fire rules and assigns singleton values to each output variable. A single defuzzifier is deployed to adjust the speed of actuator: the kitchen exhaust fan. The model is implemented and verified using a microcontroller by utilizing its pulse-width modulation (PWM) capabilities. Comparative analysis of the results confirms the high accuracy of the proposed model which yields a maximum relative error of ~ 1 % between the model designed outputs and corresponding measured duty cycles of output pulses generated by the microcontroller. The rotations per minute (RPM) of 12 V dc fan, however, show a maximum relative error up to ~ 8 % due to its intrinsic non-linear behavior with respect to the duty cycle of input pulses.\",\"PeriodicalId\":429384,\"journal\":{\"name\":\"2019 International Conference on Robotics and Automation in Industry (ICRAI)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 International Conference on Robotics and Automation in Industry (ICRAI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICRAI47710.2019.8967397\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 International Conference on Robotics and Automation in Industry (ICRAI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICRAI47710.2019.8967397","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Low Cost and Energy Efficient Fuzzy based Kitchen Ventilation Control System
In this paper, a kitchen ventilation control system is modeled using fuzzy system-modeling technique and implemented through a microcontroller. Based on the Mamdani’s model, the designed fuzzy kitchen ventilation system accepts four crisp input values from Stove Heating, Cooking Fumes, Humidity, and Temperature sensors; divides the treatise into sections, each with two fuzzy variables; fire rules and assigns singleton values to each output variable. A single defuzzifier is deployed to adjust the speed of actuator: the kitchen exhaust fan. The model is implemented and verified using a microcontroller by utilizing its pulse-width modulation (PWM) capabilities. Comparative analysis of the results confirms the high accuracy of the proposed model which yields a maximum relative error of ~ 1 % between the model designed outputs and corresponding measured duty cycles of output pulses generated by the microcontroller. The rotations per minute (RPM) of 12 V dc fan, however, show a maximum relative error up to ~ 8 % due to its intrinsic non-linear behavior with respect to the duty cycle of input pulses.