{"title":"Design of robust intelligent control of manipulators","authors":"A. García-Cerezo, A. Barreiro, A. Ollero","doi":"10.1109/ICSYSE.1991.161119","DOIUrl":null,"url":null,"abstract":"Robot manipulator control incorporating heuristic rules is considered. Fuzzy logic is used to model heuristic knowledge. Nonlinear stability criteria are applied to guarantee the stability of the control of the control system. The analysis and design of the intelligent control system is carried out by means of the conicity stability criterion. By using this criterion it is possible to find and modify the critical rules influencing stability. A Scara robot is considered, and the robustness of a fuzzy controller is shown. The results can be easily extended when using other techniques to model the heuristic adaptive and learning control schemes.<<ETX>>","PeriodicalId":250037,"journal":{"name":"IEEE 1991 International Conference on Systems Engineering","volume":"139 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE 1991 International Conference on Systems Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSYSE.1991.161119","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 8
Abstract
Robot manipulator control incorporating heuristic rules is considered. Fuzzy logic is used to model heuristic knowledge. Nonlinear stability criteria are applied to guarantee the stability of the control of the control system. The analysis and design of the intelligent control system is carried out by means of the conicity stability criterion. By using this criterion it is possible to find and modify the critical rules influencing stability. A Scara robot is considered, and the robustness of a fuzzy controller is shown. The results can be easily extended when using other techniques to model the heuristic adaptive and learning control schemes.<>