{"title":"Implementation of Fuzzy NARX IMC PID control of PAM robot arm using Modified Genetic Algorithms","authors":"H. Anh","doi":"10.1109/GEFS.2011.5949491","DOIUrl":null,"url":null,"abstract":"In this paper, a proposed Fuzzy Nonlinear ARX (NARX) model is applied to model, identify and control the highly nonlinear pneumatic artificial muscle (PAM) robot arm. The Fuzzy NARX models are then applied as inverse and forward Fuzzy NARX models in the novel Fuzzy NARX IMC-PID controller for adaptively tracking the joint angle position of the nonlinear PAM robot arm. The performance of the proposed controller is due to the combination between the robust internal model control (IMC) structure with the approximating and predictive potentiality of the Fuzzy NARX model. The experimental testings are carried out and the effectiveness of the proposed control algorithm is demonstrated with two different conditions of payload and two kinds of control methods. These results can also be applied to control the other highly nonlinear and time-varying parametric industrial robot systems.","PeriodicalId":120918,"journal":{"name":"2011 IEEE 5th International Workshop on Genetic and Evolutionary Fuzzy Systems (GEFS)","volume":"18 5","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 IEEE 5th International Workshop on Genetic and Evolutionary Fuzzy Systems (GEFS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/GEFS.2011.5949491","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
In this paper, a proposed Fuzzy Nonlinear ARX (NARX) model is applied to model, identify and control the highly nonlinear pneumatic artificial muscle (PAM) robot arm. The Fuzzy NARX models are then applied as inverse and forward Fuzzy NARX models in the novel Fuzzy NARX IMC-PID controller for adaptively tracking the joint angle position of the nonlinear PAM robot arm. The performance of the proposed controller is due to the combination between the robust internal model control (IMC) structure with the approximating and predictive potentiality of the Fuzzy NARX model. The experimental testings are carried out and the effectiveness of the proposed control algorithm is demonstrated with two different conditions of payload and two kinds of control methods. These results can also be applied to control the other highly nonlinear and time-varying parametric industrial robot systems.
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