基于模型识别方法的机械臂动力学建模与鲁棒控制

IF 1.5 Q2 COMPUTER SCIENCE, THEORY & METHODS
Y. Ge, Jing Zhang
{"title":"基于模型识别方法的机械臂动力学建模与鲁棒控制","authors":"Y. Ge, Jing Zhang","doi":"10.3233/JIFS-219069","DOIUrl":null,"url":null,"abstract":"This paper analyzes the dynamics modelling and robust control of the robotic arm by using a model-based defines method. Firstly, the motion coupling relationship between the front and rear joints of the robotic arm is analyzed, and two kinds of motion decoupling modules based on planetary gear and pulley system are proposed, and the decoupling principle of the motion decoupling module is analyzed to realize the mechanical decoupling of the joint motion of the robotic arm. After that, a comprehensive test bench of two-degree-of-freedom robotic arm joint motion is constructed, and the factors influencing the decoupling effect of the mechanical decoupling module are analyzed through experiments to verify the effectiveness of the motion decoupling module. At the same time, the analysis also shows that: with the increase of the number of robotic arm joints, the number and volume of required decoupling modules increase, and the application of decoupling modules will significantly increase the volume, weight, and torque loss of the robotic arm, thus leading to the robotic arm’s large load to weight ratio which is not an advantage, therefore, mechanical decoupling is not suitable for robotic arms with more than 3 degrees of freedom. The design of a fuzzy incremental controller based on the model dialectic method is proposed for application in parallel robot control; it has universal approximation characteristics and can self-organize the velocity and position information of the parallel robot legs, and dynamically adjust the output of the controller by the designed affiliation function and control rules.","PeriodicalId":44705,"journal":{"name":"International Journal of Fuzzy Logic and Intelligent Systems","volume":null,"pages":null},"PeriodicalIF":1.5000,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Robotic arm dynamics modelling and robust control based on model recognition method\",\"authors\":\"Y. Ge, Jing Zhang\",\"doi\":\"10.3233/JIFS-219069\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper analyzes the dynamics modelling and robust control of the robotic arm by using a model-based defines method. Firstly, the motion coupling relationship between the front and rear joints of the robotic arm is analyzed, and two kinds of motion decoupling modules based on planetary gear and pulley system are proposed, and the decoupling principle of the motion decoupling module is analyzed to realize the mechanical decoupling of the joint motion of the robotic arm. After that, a comprehensive test bench of two-degree-of-freedom robotic arm joint motion is constructed, and the factors influencing the decoupling effect of the mechanical decoupling module are analyzed through experiments to verify the effectiveness of the motion decoupling module. At the same time, the analysis also shows that: with the increase of the number of robotic arm joints, the number and volume of required decoupling modules increase, and the application of decoupling modules will significantly increase the volume, weight, and torque loss of the robotic arm, thus leading to the robotic arm’s large load to weight ratio which is not an advantage, therefore, mechanical decoupling is not suitable for robotic arms with more than 3 degrees of freedom. The design of a fuzzy incremental controller based on the model dialectic method is proposed for application in parallel robot control; it has universal approximation characteristics and can self-organize the velocity and position information of the parallel robot legs, and dynamically adjust the output of the controller by the designed affiliation function and control rules.\",\"PeriodicalId\":44705,\"journal\":{\"name\":\"International Journal of Fuzzy Logic and Intelligent Systems\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.5000,\"publicationDate\":\"2021-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Fuzzy Logic and Intelligent Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.3233/JIFS-219069\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"COMPUTER SCIENCE, THEORY & METHODS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Fuzzy Logic and Intelligent Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3233/JIFS-219069","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, THEORY & METHODS","Score":null,"Total":0}
引用次数: 1

摘要

采用基于模型的定义方法,对机械臂的动力学建模和鲁棒控制进行了分析。首先,分析了机械臂前后关节之间的运动耦合关系,提出了基于行星齿轮和滑轮系统的两种运动解耦模块,并分析了运动解耦模块的解耦原理,实现了机械臂关节运动的机械解耦。随后搭建了二自由度机械臂关节运动综合试验台,通过实验分析了机械解耦模块解耦效果的影响因素,验证了运动解耦模块的有效性。同时,分析还表明:随着机械臂关节数量的增加,所需解耦模块的数量和体积也随之增加,解耦模块的应用将显著增加机械臂的体积、重量和扭矩损失,从而导致机械臂的负载重量比大并不是一种优势,因此,机械解耦不适用于3个以上自由度的机械臂。针对并联机器人的控制问题,提出了一种基于模型辩证法的模糊增量控制器设计;该方法具有通用逼近特性,能够自组织并联机器人腿的速度和位置信息,并根据设计的隶属函数和控制规则动态调整控制器的输出。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Robotic arm dynamics modelling and robust control based on model recognition method
This paper analyzes the dynamics modelling and robust control of the robotic arm by using a model-based defines method. Firstly, the motion coupling relationship between the front and rear joints of the robotic arm is analyzed, and two kinds of motion decoupling modules based on planetary gear and pulley system are proposed, and the decoupling principle of the motion decoupling module is analyzed to realize the mechanical decoupling of the joint motion of the robotic arm. After that, a comprehensive test bench of two-degree-of-freedom robotic arm joint motion is constructed, and the factors influencing the decoupling effect of the mechanical decoupling module are analyzed through experiments to verify the effectiveness of the motion decoupling module. At the same time, the analysis also shows that: with the increase of the number of robotic arm joints, the number and volume of required decoupling modules increase, and the application of decoupling modules will significantly increase the volume, weight, and torque loss of the robotic arm, thus leading to the robotic arm’s large load to weight ratio which is not an advantage, therefore, mechanical decoupling is not suitable for robotic arms with more than 3 degrees of freedom. The design of a fuzzy incremental controller based on the model dialectic method is proposed for application in parallel robot control; it has universal approximation characteristics and can self-organize the velocity and position information of the parallel robot legs, and dynamically adjust the output of the controller by the designed affiliation function and control rules.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
CiteScore
2.80
自引率
23.10%
发文量
31
期刊介绍: The International Journal of Fuzzy Logic and Intelligent Systems (pISSN 1598-2645, eISSN 2093-744X) is published quarterly by the Korean Institute of Intelligent Systems. The official title of the journal is International Journal of Fuzzy Logic and Intelligent Systems and the abbreviated title is Int. J. Fuzzy Log. Intell. Syst. Some, or all, of the articles in the journal are indexed in SCOPUS, Korea Citation Index (KCI), DOI/CrossrRef, DBLP, and Google Scholar. The journal was launched in 2001 and dedicated to the dissemination of well-defined theoretical and empirical studies results that have a potential impact on the realization of intelligent systems based on fuzzy logic and intelligent systems theory. Specific topics include, but are not limited to: a) computational intelligence techniques including fuzzy logic systems, neural networks and evolutionary computation; b) intelligent control, instrumentation and robotics; c) adaptive signal and multimedia processing; d) intelligent information processing including pattern recognition and information processing; e) machine learning and smart systems including data mining and intelligent service practices; f) fuzzy theory and its applications.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信