{"title":"一种随墙移动机器人增益调度模糊控制器","authors":"Khaled F. Aljanaideh, K. Demirli","doi":"10.1109/NAFIPS.2010.5548198","DOIUrl":null,"url":null,"abstract":"Tuning membership functions parameters of fuzzy logic controllers (FLC) has proven to be an effective method in improving the performance of this type of controllers. However, simulations usually require a considerable amount of time to optimize the membership functions parameters. In this paper a new methodology is proposed to optimize the performance of the FLC. The FLC in this paper is simply designed. The gain scheduling controller will be used before the FLC to control the error signal by multiplying it by a certain gain. The value of this gain depends on the value of the error. The proposed method is applied to a wall following mobile robot to ensure its capability to improve the performance of the fuzzy logic controller. Computer simulations are carried out to compare between a Knowledge Based Fuzzy Logic Controller (KBFLC), an optimized KBFLC and our proposed model.","PeriodicalId":394892,"journal":{"name":"2010 Annual Meeting of the North American Fuzzy Information Processing Society","volume":"12 3","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Gain scheduling fuzzy logic controller for a wall-following mobile robot\",\"authors\":\"Khaled F. Aljanaideh, K. Demirli\",\"doi\":\"10.1109/NAFIPS.2010.5548198\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Tuning membership functions parameters of fuzzy logic controllers (FLC) has proven to be an effective method in improving the performance of this type of controllers. However, simulations usually require a considerable amount of time to optimize the membership functions parameters. In this paper a new methodology is proposed to optimize the performance of the FLC. The FLC in this paper is simply designed. The gain scheduling controller will be used before the FLC to control the error signal by multiplying it by a certain gain. The value of this gain depends on the value of the error. The proposed method is applied to a wall following mobile robot to ensure its capability to improve the performance of the fuzzy logic controller. Computer simulations are carried out to compare between a Knowledge Based Fuzzy Logic Controller (KBFLC), an optimized KBFLC and our proposed model.\",\"PeriodicalId\":394892,\"journal\":{\"name\":\"2010 Annual Meeting of the North American Fuzzy Information Processing Society\",\"volume\":\"12 3\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-07-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 Annual Meeting of the North American Fuzzy Information Processing Society\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/NAFIPS.2010.5548198\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 Annual Meeting of the North American Fuzzy Information Processing Society","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NAFIPS.2010.5548198","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Gain scheduling fuzzy logic controller for a wall-following mobile robot
Tuning membership functions parameters of fuzzy logic controllers (FLC) has proven to be an effective method in improving the performance of this type of controllers. However, simulations usually require a considerable amount of time to optimize the membership functions parameters. In this paper a new methodology is proposed to optimize the performance of the FLC. The FLC in this paper is simply designed. The gain scheduling controller will be used before the FLC to control the error signal by multiplying it by a certain gain. The value of this gain depends on the value of the error. The proposed method is applied to a wall following mobile robot to ensure its capability to improve the performance of the fuzzy logic controller. Computer simulations are carried out to compare between a Knowledge Based Fuzzy Logic Controller (KBFLC), an optimized KBFLC and our proposed model.