Kinematics Model Optimization Algorithm for Six Degrees of Freedom Parallel Platform
The attitude closed-loop control of the parallel platform in the working space needs to determine the relationship between the pose of the top moving platform and the length of each mechanical arm, that is, the kinematics problem of the parallel platform. In this study, the kinematics model of the s...
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| Format: | Article |
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MDPI AG
2023-02-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/13/5/3082 |
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| author | Mingzhe Liu Qiuxiang Gu Bo Yang Zhengtong Yin Shan Liu Lirong Yin Wenfeng Zheng |
| author_facet | Mingzhe Liu Qiuxiang Gu Bo Yang Zhengtong Yin Shan Liu Lirong Yin Wenfeng Zheng |
| author_sort | Mingzhe Liu |
| collection | DOAJ |
| description | The attitude closed-loop control of the parallel platform in the working space needs to determine the relationship between the pose of the top moving platform and the length of each mechanical arm, that is, the kinematics problem of the parallel platform. In this study, the kinematics model of the six-degree-of-freedom parallel platform was established. The kinematics forward solution algorithm based on Newton–Raphson iteration was studied. The kinematics forward solution method usually adopts a numerical solution, which often needs multiple iterations, and the algorithm has a poor real-time performance. In order to improve the real-time performance of the parallel platform control system, a multivariate polynomial regression kinematics forward solution algorithm is proposed in this paper. Moreover, by combining the multivariate polynomial regression with the Newton iterative method, we obtained an efficient solution algorithm with controllable solution accuracy. The effectiveness of the proposed method was verified by simulation tests and physical tests. |
| first_indexed | 2024-03-11T07:31:16Z |
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| id | doaj.art-e57e232c99e94b838b1adf79b6a6d514 |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-11T07:31:16Z |
| publishDate | 2023-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-e57e232c99e94b838b1adf79b6a6d5142023-11-17T07:18:58ZengMDPI AGApplied Sciences2076-34172023-02-01135308210.3390/app13053082Kinematics Model Optimization Algorithm for Six Degrees of Freedom Parallel PlatformMingzhe Liu0Qiuxiang Gu1Bo Yang2Zhengtong Yin3Shan Liu4Lirong Yin5Wenfeng Zheng6School of Data Science and Artificial Intelligence, Wenzhou University of Technology, Wenzhou 325000, ChinaSchool of Automation, University of Electronic Science and Technology of China, Chengdu 610054, ChinaSchool of Automation, University of Electronic Science and Technology of China, Chengdu 610054, ChinaCollege of Resource and Environment Engineering, Guizhou University, Guiyang 550025, ChinaSchool of Automation, University of Electronic Science and Technology of China, Chengdu 610054, ChinaDepartment of Geography and Anthropology, Louisiana State University, Baton Rouge, LA 70803, USASchool of Automation, University of Electronic Science and Technology of China, Chengdu 610054, ChinaThe attitude closed-loop control of the parallel platform in the working space needs to determine the relationship between the pose of the top moving platform and the length of each mechanical arm, that is, the kinematics problem of the parallel platform. In this study, the kinematics model of the six-degree-of-freedom parallel platform was established. The kinematics forward solution algorithm based on Newton–Raphson iteration was studied. The kinematics forward solution method usually adopts a numerical solution, which often needs multiple iterations, and the algorithm has a poor real-time performance. In order to improve the real-time performance of the parallel platform control system, a multivariate polynomial regression kinematics forward solution algorithm is proposed in this paper. Moreover, by combining the multivariate polynomial regression with the Newton iterative method, we obtained an efficient solution algorithm with controllable solution accuracy. The effectiveness of the proposed method was verified by simulation tests and physical tests.https://www.mdpi.com/2076-3417/13/5/3082parallel platformmultivariate polynomial regressionNewton iterativekinematics |
| spellingShingle | Mingzhe Liu Qiuxiang Gu Bo Yang Zhengtong Yin Shan Liu Lirong Yin Wenfeng Zheng Kinematics Model Optimization Algorithm for Six Degrees of Freedom Parallel Platform Applied Sciences parallel platform multivariate polynomial regression Newton iterative kinematics |
| title | Kinematics Model Optimization Algorithm for Six Degrees of Freedom Parallel Platform |
| title_full | Kinematics Model Optimization Algorithm for Six Degrees of Freedom Parallel Platform |
| title_fullStr | Kinematics Model Optimization Algorithm for Six Degrees of Freedom Parallel Platform |
| title_full_unstemmed | Kinematics Model Optimization Algorithm for Six Degrees of Freedom Parallel Platform |
| title_short | Kinematics Model Optimization Algorithm for Six Degrees of Freedom Parallel Platform |
| title_sort | kinematics model optimization algorithm for six degrees of freedom parallel platform |
| topic | parallel platform multivariate polynomial regression Newton iterative kinematics |
| url | https://www.mdpi.com/2076-3417/13/5/3082 |
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