{"title":"基于自适应神经模糊推理系统的机械臂控制","authors":"D. Adhyaru, J. Patel, Rishi Gianchandani","doi":"10.1109/ICMET.2010.5598379","DOIUrl":null,"url":null,"abstract":"Robot manipulators have become increasingly important in the field of flexible automation. Through the years considerable research effort has been made in their controller design. In order to achieve accurate trajectory tracking and good control performance, a number of control schemes have been developed. Amongst these, ANFIS (Adaptive Neuro-Fuzzy Inference System) has provided best results for control of robotic manipulators as compared to the conventional control strategies.","PeriodicalId":415118,"journal":{"name":"2010 International Conference on Mechanical and Electrical Technology","volume":"16 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":"{\"title\":\"Adaptive Neuro-Fuzzy Inference System based control of robotic manipulators\",\"authors\":\"D. Adhyaru, J. Patel, Rishi Gianchandani\",\"doi\":\"10.1109/ICMET.2010.5598379\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Robot manipulators have become increasingly important in the field of flexible automation. Through the years considerable research effort has been made in their controller design. In order to achieve accurate trajectory tracking and good control performance, a number of control schemes have been developed. Amongst these, ANFIS (Adaptive Neuro-Fuzzy Inference System) has provided best results for control of robotic manipulators as compared to the conventional control strategies.\",\"PeriodicalId\":415118,\"journal\":{\"name\":\"2010 International Conference on Mechanical and Electrical Technology\",\"volume\":\"16 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-10-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"10\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 International Conference on Mechanical and Electrical Technology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICMET.2010.5598379\",\"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 International Conference on Mechanical and Electrical Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICMET.2010.5598379","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Adaptive Neuro-Fuzzy Inference System based control of robotic manipulators
Robot manipulators have become increasingly important in the field of flexible automation. Through the years considerable research effort has been made in their controller design. In order to achieve accurate trajectory tracking and good control performance, a number of control schemes have been developed. Amongst these, ANFIS (Adaptive Neuro-Fuzzy Inference System) has provided best results for control of robotic manipulators as compared to the conventional control strategies.
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