M. Ivanescu, N. Bîzdoaca, D. Cojocaru, N. Popescu, D. Popescu
{"title":"A Fuzzy Controller for Tentacle Cooperative Robots","authors":"M. Ivanescu, N. Bîzdoaca, D. Cojocaru, N. Popescu, D. Popescu","doi":"10.1115/imece2001/dsc-24631","DOIUrl":null,"url":null,"abstract":"\n A fuzzy system and the control algorithms are proposed to solve the control multi-chain robotic system formed by tentacle manipulators grasping a commune object with hard contact points. The control system contains two parts: the first component is a conventional controller, which implements a control strategy based on the Lyapunov stability, and the second is an adaptive fuzzy controller which adjusts the control parameters by the output of the first level controller. The stability and robustness is investigated and the fuzzy rules are established The fuzzy controller was developed using Matlab and Simulink software. Simulation results are presented and discussed.","PeriodicalId":90691,"journal":{"name":"Proceedings of the ASME Dynamic Systems and Control Conference. ASME Dynamic Systems and Control Conference","volume":"39 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2001-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the ASME Dynamic Systems and Control Conference. ASME Dynamic Systems and Control Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1115/imece2001/dsc-24631","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
A fuzzy system and the control algorithms are proposed to solve the control multi-chain robotic system formed by tentacle manipulators grasping a commune object with hard contact points. The control system contains two parts: the first component is a conventional controller, which implements a control strategy based on the Lyapunov stability, and the second is an adaptive fuzzy controller which adjusts the control parameters by the output of the first level controller. The stability and robustness is investigated and the fuzzy rules are established The fuzzy controller was developed using Matlab and Simulink software. Simulation results are presented and discussed.