{"title":"基于模糊逻辑的移动机器人预测控制器","authors":"Nguyen Truong Thinh, Nguyen Trong Tuan, L. Hưng","doi":"10.1109/GTSD.2016.41","DOIUrl":null,"url":null,"abstract":"In this paper a control design of a non-holonomic mobile robot with a differential drive is presented based on a new behavior-based fuzzy control method. Automatic control of a mobile robot depends on complex signal processing mechanisms. It is based on behavioral architecture which can deal with uncertainties in unknown environments and has the ability to accommodate different behaviors. Basic behaviors are controlled by specific fuzzy logic controllers. The proposed approach qualifies for driving a robot to reach a target while avoiding obstacles in the dynamic environment. Simulation and experiments are performed to verify the correctness and feasibility of the proposed method. The experiment results demonstrated the feasibility and advantages of this predictive fuzzy control on the trajectory tracking of a mobile robot.","PeriodicalId":340479,"journal":{"name":"2016 3rd International Conference on Green Technology and Sustainable Development (GTSD)","volume":"111 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Predictive Controller for Mobile Robot Based on Fuzzy Logic\",\"authors\":\"Nguyen Truong Thinh, Nguyen Trong Tuan, L. Hưng\",\"doi\":\"10.1109/GTSD.2016.41\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper a control design of a non-holonomic mobile robot with a differential drive is presented based on a new behavior-based fuzzy control method. Automatic control of a mobile robot depends on complex signal processing mechanisms. It is based on behavioral architecture which can deal with uncertainties in unknown environments and has the ability to accommodate different behaviors. Basic behaviors are controlled by specific fuzzy logic controllers. The proposed approach qualifies for driving a robot to reach a target while avoiding obstacles in the dynamic environment. Simulation and experiments are performed to verify the correctness and feasibility of the proposed method. The experiment results demonstrated the feasibility and advantages of this predictive fuzzy control on the trajectory tracking of a mobile robot.\",\"PeriodicalId\":340479,\"journal\":{\"name\":\"2016 3rd International Conference on Green Technology and Sustainable Development (GTSD)\",\"volume\":\"111 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 3rd International Conference on Green Technology and Sustainable Development (GTSD)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/GTSD.2016.41\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 3rd International Conference on Green Technology and Sustainable Development (GTSD)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/GTSD.2016.41","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Predictive Controller for Mobile Robot Based on Fuzzy Logic
In this paper a control design of a non-holonomic mobile robot with a differential drive is presented based on a new behavior-based fuzzy control method. Automatic control of a mobile robot depends on complex signal processing mechanisms. It is based on behavioral architecture which can deal with uncertainties in unknown environments and has the ability to accommodate different behaviors. Basic behaviors are controlled by specific fuzzy logic controllers. The proposed approach qualifies for driving a robot to reach a target while avoiding obstacles in the dynamic environment. Simulation and experiments are performed to verify the correctness and feasibility of the proposed method. The experiment results demonstrated the feasibility and advantages of this predictive fuzzy control on the trajectory tracking of a mobile robot.