{"title":"Intelligent control of four DOF robotic arm","authors":"Neelu Nagpal, B. Bhushan, Vijyant Agarwal","doi":"10.1109/ICPEICES.2016.7853357","DOIUrl":null,"url":null,"abstract":"In this paper; Fuzzy control and Adaptive Network based Fuzzy Interference System (ANFIS) techniques have been investigated for decentralised joint position control of an four DOF robotic arm for desired motion. Four different types of membership functions like Triangular; Pi; Gaussian; Dsigmf are implemented in the fuzzy PD and ANFIS controller. The performance of controller is evaluated and compared in terms of maximum overshoot; settling time and steady state error with conventional PID controller. Simulation results and comparative analysis validates the effectiveness of Fuzzy and ANFIS based controller with the proper selection of membership function for improving the system performance and reducing position tracking error.","PeriodicalId":305942,"journal":{"name":"2016 IEEE 1st International Conference on Power Electronics, Intelligent Control and Energy Systems (ICPEICES)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE 1st International Conference on Power Electronics, Intelligent Control and Energy Systems (ICPEICES)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICPEICES.2016.7853357","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
In this paper; Fuzzy control and Adaptive Network based Fuzzy Interference System (ANFIS) techniques have been investigated for decentralised joint position control of an four DOF robotic arm for desired motion. Four different types of membership functions like Triangular; Pi; Gaussian; Dsigmf are implemented in the fuzzy PD and ANFIS controller. The performance of controller is evaluated and compared in terms of maximum overshoot; settling time and steady state error with conventional PID controller. Simulation results and comparative analysis validates the effectiveness of Fuzzy and ANFIS based controller with the proper selection of membership function for improving the system performance and reducing position tracking error.
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