{"title":"基于模糊逻辑和神经模糊方法的移动机器人墙体监测行为控制","authors":"Hanene Rouabah, C. Abdelmoula, M. Masmoudi","doi":"10.1109/DTIS.2012.6232944","DOIUrl":null,"url":null,"abstract":"This work describes the design and development of controllers based on artificial intelligence tried on a newly design of a mobile robot type-vehicle to control behavior for monitoring wall. Two approaches have been optimized and developed to control the robot: The first one is based on Fuzzy logic. This control algorithm combines the different sensory information and provides a suitable control command allowing the mobile robot to follow the wall deviations. The second approach consists of applying a hybrid-type Neuro-Fuzzy ANFIS controller for the same task. This controller combines the advantages of Fuzzy logic and Neural Networks. Simulations results are presented and implemented with VHDL using ANFIS architecture.","PeriodicalId":114829,"journal":{"name":"7th International Conference on Design & Technology of Integrated Systems in Nanoscale Era","volume":"28 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"Behavior control of a mobile robot based on Fuzzy logic and Neuro Fuzzy approaches for monitoring wall\",\"authors\":\"Hanene Rouabah, C. Abdelmoula, M. Masmoudi\",\"doi\":\"10.1109/DTIS.2012.6232944\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This work describes the design and development of controllers based on artificial intelligence tried on a newly design of a mobile robot type-vehicle to control behavior for monitoring wall. Two approaches have been optimized and developed to control the robot: The first one is based on Fuzzy logic. This control algorithm combines the different sensory information and provides a suitable control command allowing the mobile robot to follow the wall deviations. The second approach consists of applying a hybrid-type Neuro-Fuzzy ANFIS controller for the same task. This controller combines the advantages of Fuzzy logic and Neural Networks. Simulations results are presented and implemented with VHDL using ANFIS architecture.\",\"PeriodicalId\":114829,\"journal\":{\"name\":\"7th International Conference on Design & Technology of Integrated Systems in Nanoscale Era\",\"volume\":\"28 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-05-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"7th International Conference on Design & Technology of Integrated Systems in Nanoscale Era\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/DTIS.2012.6232944\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"7th International Conference on Design & Technology of Integrated Systems in Nanoscale Era","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DTIS.2012.6232944","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Behavior control of a mobile robot based on Fuzzy logic and Neuro Fuzzy approaches for monitoring wall
This work describes the design and development of controllers based on artificial intelligence tried on a newly design of a mobile robot type-vehicle to control behavior for monitoring wall. Two approaches have been optimized and developed to control the robot: The first one is based on Fuzzy logic. This control algorithm combines the different sensory information and provides a suitable control command allowing the mobile robot to follow the wall deviations. The second approach consists of applying a hybrid-type Neuro-Fuzzy ANFIS controller for the same task. This controller combines the advantages of Fuzzy logic and Neural Networks. Simulations results are presented and implemented with VHDL using ANFIS architecture.