{"title":"模糊逻辑在消防机器人中的实现","authors":"Budi Kustamtomo, A. Triwiyatno, M. Riyadi","doi":"10.1109/ISITIA52817.2021.9502242","DOIUrl":null,"url":null,"abstract":"A fire fighting robot is a robot that uses a fire sensor and is equipped with a extinguisher to detect fires and extinguish them. Tracking fires requires not only a fire sensor, but also a combination with other methods that can optimize the process. Fuzzy does not require a mathematical model of the system to be controlled. This is one of the advantages so that the design of the controller is easier to do by relying only on logic rules. Fuzzy system in this study has inputs in the form of error and delta error resulting from processing angle degree sensor robot and fuzzy output in the form of duty cycle used to set the speed of the right and left wheels of the robot towards the fire point. From the tests conducted, the average rise time was 1.8 seconds, then overshoot of 19.5% and was able to reach steady state with a time of 3 seconds. The robot was also able to track and extinguish fires with an average success percentage of 99.5% of 10 tests per room, with an average time in room 1 of 4.5 seconds, in room 2 of 10.4 seconds, in room 3 of 16.4seconds, and in free room of 4.9 seconds.","PeriodicalId":161240,"journal":{"name":"2021 International Seminar on Intelligent Technology and Its Applications (ISITIA)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Implementation of Fuzzy Logic on Fire Fighting Robots\",\"authors\":\"Budi Kustamtomo, A. Triwiyatno, M. Riyadi\",\"doi\":\"10.1109/ISITIA52817.2021.9502242\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A fire fighting robot is a robot that uses a fire sensor and is equipped with a extinguisher to detect fires and extinguish them. Tracking fires requires not only a fire sensor, but also a combination with other methods that can optimize the process. Fuzzy does not require a mathematical model of the system to be controlled. This is one of the advantages so that the design of the controller is easier to do by relying only on logic rules. Fuzzy system in this study has inputs in the form of error and delta error resulting from processing angle degree sensor robot and fuzzy output in the form of duty cycle used to set the speed of the right and left wheels of the robot towards the fire point. From the tests conducted, the average rise time was 1.8 seconds, then overshoot of 19.5% and was able to reach steady state with a time of 3 seconds. The robot was also able to track and extinguish fires with an average success percentage of 99.5% of 10 tests per room, with an average time in room 1 of 4.5 seconds, in room 2 of 10.4 seconds, in room 3 of 16.4seconds, and in free room of 4.9 seconds.\",\"PeriodicalId\":161240,\"journal\":{\"name\":\"2021 International Seminar on Intelligent Technology and Its Applications (ISITIA)\",\"volume\":\"31 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-07-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 International Seminar on Intelligent Technology and Its Applications (ISITIA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISITIA52817.2021.9502242\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 International Seminar on Intelligent Technology and Its Applications (ISITIA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISITIA52817.2021.9502242","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Implementation of Fuzzy Logic on Fire Fighting Robots
A fire fighting robot is a robot that uses a fire sensor and is equipped with a extinguisher to detect fires and extinguish them. Tracking fires requires not only a fire sensor, but also a combination with other methods that can optimize the process. Fuzzy does not require a mathematical model of the system to be controlled. This is one of the advantages so that the design of the controller is easier to do by relying only on logic rules. Fuzzy system in this study has inputs in the form of error and delta error resulting from processing angle degree sensor robot and fuzzy output in the form of duty cycle used to set the speed of the right and left wheels of the robot towards the fire point. From the tests conducted, the average rise time was 1.8 seconds, then overshoot of 19.5% and was able to reach steady state with a time of 3 seconds. The robot was also able to track and extinguish fires with an average success percentage of 99.5% of 10 tests per room, with an average time in room 1 of 4.5 seconds, in room 2 of 10.4 seconds, in room 3 of 16.4seconds, and in free room of 4.9 seconds.