{"title":"A switching control based fuzzy energy region method for underactuated robots","authors":"K. Ichida, K. Izumi, K. Watanabe","doi":"10.1109/ARSO.2005.1511649","DOIUrl":null,"url":null,"abstract":"One of control methods for underactuated manipulators is known as a switching control which selects a partially-stable controller using a prespecified switching rule. A switching computed torque control with a fuzzy energy region method has been already proposed. In this approach, some partly stable controllers are designed by the computed torque method, and a switching rule is based on fuzzy energy regions. Design parameters related to boundary curves of fuzzy energy regions are optimized offline by a genetic algorithm (GA). In this paper, we discuss about the controlled system using the proposed method with parameters designed by GA.","PeriodicalId":443174,"journal":{"name":"IEEE Workshop on Advanced Robotics and its Social Impacts, 2005.","volume":"109 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2005-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Workshop on Advanced Robotics and its Social Impacts, 2005.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ARSO.2005.1511649","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 10
Abstract
One of control methods for underactuated manipulators is known as a switching control which selects a partially-stable controller using a prespecified switching rule. A switching computed torque control with a fuzzy energy region method has been already proposed. In this approach, some partly stable controllers are designed by the computed torque method, and a switching rule is based on fuzzy energy regions. Design parameters related to boundary curves of fuzzy energy regions are optimized offline by a genetic algorithm (GA). In this paper, we discuss about the controlled system using the proposed method with parameters designed by GA.