Kinematics Model Optimization Algorithm for Six Degrees of Freedom Parallel Platform

被引:73
作者
Liu, Mingzhe [1 ]
Gu, Qiuxiang [2 ]
Yang, Bo [2 ]
Yin, Zhengtong [3 ]
Liu, Shan [2 ]
Yin, Lirong [4 ]
Zheng, Wenfeng [2 ]
机构
[1] Wenzhou Univ Technol, Sch Data Sci & Artificial Intelligence, Wenzhou 325000, Peoples R China
[2] Univ Elect Sci & Technol China, Sch Automat, Chengdu 610054, Peoples R China
[3] Guizhou Univ, Coll Resource & Environm Engn, Guiyang 550025, Peoples R China
[4] Louisiana State Univ, Dept Geog & Anthropol, Baton Rouge, LA 70803 USA
来源
APPLIED SCIENCES-BASEL | 2023年 / 13卷 / 05期
关键词
parallel platform; multivariate polynomial regression; Newton iterative; kinematics; STEWART PLATFORM; INVERSE DYNAMICS; MANIPULATOR; ROBOT; SIMULATION;
D O I
10.3390/app13053082
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
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.
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页数:18
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