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Multi-Objective Optimization of 1T2R Parallel Mechanisms Without Fixed Orientation Center and Axis Under the Influence of Parameter Perturbation

Authors :
Yang Qi
Yu Wang
Hong Wang
Source :
IEEE Access, Vol 11, Pp 34958-34967 (2023)
Publication Year :
2023
Publisher :
IEEE, 2023.

Abstract

To track moving targets and signals in space, multiple characteristics as large orientational workspace and excellent kinematic performance are required for the satellite antenna driving mechanism. Due to variable orientational center and axes, the 3-RSR mechanism is capable of 1T2R with continuous workspace and becomes a promising solution for the satellite antenna driving mechanism. Influenced by the topological structure characteristics as none fixed orientation center and axes, the performances of 3-RSR mechanism are significantly impacted by the parameter perturbation. According to the differential mapping between finite screw and instantaneous screw, the structure, kinematics, performance, and optimization are unified under the FIS theory. To be applied for the satellite antenna driving mechanism, this paper carries out the multi-objective optimization of 3-RSR mechanism under the influence of parameter perturbation based on the FIS theory. Firstly, the orientational workspace is obtained by finite screw and the instantaneous motion description of the mechanism is derived through calculation principle of FIS theory. Secondly, the orientational workspace and kinematics indices of the mechanism are proposed towards the actual requirements of the satellite antenna driving, and the relationship with the parameters is established. The discrete operation becomes extremely complex owing to parameter perturbation, and the RSMs (response surface model) of indices without considering and considering parameter perturbation are modeled. The multi-objectives optimization of 3-RSR mechanism influenced by parameter perturbation is carried out and its Pareto frontier is obtained. Finally, a point preferred strategy is proposed and the optimum value of the parameter from Pareto frontier is selected.

Details

Language :
English
ISSN :
21693536
Volume :
11
Database :
Directory of Open Access Journals
Journal :
IEEE Access
Publication Type :
Academic Journal
Accession number :
edsdoj.21013a8335cb4e65a89e3a656f20b6f2
Document Type :
article
Full Text :
https://doi.org/10.1109/ACCESS.2023.3265076