{"title":"混合动力机器人的新型多脉冲摩擦补偿策略","authors":"Jiale Han, Hongfei Cheng, Xianlei Shan, Haitao Liu, Juliang Xiao, Tian Huang","doi":"10.1016/j.mechmachtheory.2024.105726","DOIUrl":null,"url":null,"abstract":"<div><p>Friction nonlinearity near zero velocity causes substantial tracking errors during joint motion reversals. For hybrid robots, this phenomenon is further influenced by joint acceleration and robot configuration, unique characteristics of hybrid robots that can degrade the performance of traditional friction compensation methods. This paper presents a novel multi-pulse friction compensation strategy that can adapt to joint acceleration and configuration variations in hybrid robots. Bayesian Optimization is employed to automatically tune all compensation parameters. By analyzing experimental data, a potential relationship between compensation parameters and joint acceleration is explored, leading to a concise and effective method for estimating optimal parameters based on joint acceleration. In addition, the basic idea of cluster analysis is combined with a limited number of experiments to achieve online parameter-to-configuration matching. Experimental results on TriMule-200 hybrid robot demonstrate the outstanding performance of this strategy in suppressing tracking errors during velocity reversals, as well as its robustness to joint acceleration and robot configuration variations.</p></div>","PeriodicalId":49845,"journal":{"name":"Mechanism and Machine Theory","volume":null,"pages":null},"PeriodicalIF":4.5000,"publicationDate":"2024-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A novel multi-pulse friction compensation strategy for hybrid robots\",\"authors\":\"Jiale Han, Hongfei Cheng, Xianlei Shan, Haitao Liu, Juliang Xiao, Tian Huang\",\"doi\":\"10.1016/j.mechmachtheory.2024.105726\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Friction nonlinearity near zero velocity causes substantial tracking errors during joint motion reversals. For hybrid robots, this phenomenon is further influenced by joint acceleration and robot configuration, unique characteristics of hybrid robots that can degrade the performance of traditional friction compensation methods. This paper presents a novel multi-pulse friction compensation strategy that can adapt to joint acceleration and configuration variations in hybrid robots. Bayesian Optimization is employed to automatically tune all compensation parameters. By analyzing experimental data, a potential relationship between compensation parameters and joint acceleration is explored, leading to a concise and effective method for estimating optimal parameters based on joint acceleration. In addition, the basic idea of cluster analysis is combined with a limited number of experiments to achieve online parameter-to-configuration matching. Experimental results on TriMule-200 hybrid robot demonstrate the outstanding performance of this strategy in suppressing tracking errors during velocity reversals, as well as its robustness to joint acceleration and robot configuration variations.</p></div>\",\"PeriodicalId\":49845,\"journal\":{\"name\":\"Mechanism and Machine Theory\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":4.5000,\"publicationDate\":\"2024-07-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Mechanism and Machine Theory\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0094114X24001538\",\"RegionNum\":1,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENGINEERING, MECHANICAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Mechanism and Machine Theory","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0094114X24001538","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, MECHANICAL","Score":null,"Total":0}
A novel multi-pulse friction compensation strategy for hybrid robots
Friction nonlinearity near zero velocity causes substantial tracking errors during joint motion reversals. For hybrid robots, this phenomenon is further influenced by joint acceleration and robot configuration, unique characteristics of hybrid robots that can degrade the performance of traditional friction compensation methods. This paper presents a novel multi-pulse friction compensation strategy that can adapt to joint acceleration and configuration variations in hybrid robots. Bayesian Optimization is employed to automatically tune all compensation parameters. By analyzing experimental data, a potential relationship between compensation parameters and joint acceleration is explored, leading to a concise and effective method for estimating optimal parameters based on joint acceleration. In addition, the basic idea of cluster analysis is combined with a limited number of experiments to achieve online parameter-to-configuration matching. Experimental results on TriMule-200 hybrid robot demonstrate the outstanding performance of this strategy in suppressing tracking errors during velocity reversals, as well as its robustness to joint acceleration and robot configuration variations.
期刊介绍：
Mechanism and Machine Theory provides a medium of communication between engineers and scientists engaged in research and development within the fields of knowledge embraced by IFToMM, the International Federation for the Promotion of Mechanism and Machine Science, therefore affiliated with IFToMM as its official research journal.
The main topics are:
Design Theory and Methodology;
Haptics and Human-Machine-Interfaces;
Robotics, Mechatronics and Micro-Machines;
Mechanisms, Mechanical Transmissions and Machines;
Kinematics, Dynamics, and Control of Mechanical Systems;
Applications to Bioengineering and Molecular Chemistry
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