Journal Article

Error identification and compensation of 1T2R parallel power head based on trajectory optimization and principal component analysis

Lu, Wenliang, Cui, Yizhang, Jia, Shilei, Ni, Yanbing, Lu, Chenghao

2023

Overview

PurposeThe purpose of this paper is to propose a method for selecting the position and attitude trajectory of error measurement to improve the kinematic calibration efficiency of a one translational and two rotational (1T2R) parallel power head and to improve the error compensation effect by improving the properties of the error identification matrix.Design/methodology/approachFirst, a general mapping model between the endpoint synthesis error is established and each geometric error source. Second, a model for optimizing the position and attitude trajectory of error measurement based on sensitivity analysis results is proposed, providing a basis for optimizing the error measurement trajectory of the mechanism in the working space. Finally, distance error measurement information and principal component analysis (PCA) ideas are used to construct an error identification matrix. The robustness and compensation effect of the identification algorithm were verified by simulation and through experiments.FindingsThrough sensitivity analysis, it is found that the distribution of the sensitivity coefficient of each error source in the plane of the workspace can approximately represent its distribution in the workspace, and when the end of the mechanism moves in a circle with a large nutation angle, the comprehensive influence coefficient of each sensitivity is the largest. Residual analysis shows that the robustness of the identification algorithm with the idea of PCA is improved. Through experiments, it is found that the compensation effect is improved.Originality/valueA model for optimizing the position and attitude trajectory of error measurement is proposed, which can effectively improve the error measurement efficiency of the 1T2R parallel mechanism. In addition, the PCA idea is introduced. A least-squares PCA error identification algorithm that improves the robustness of the identification algorithm by improving the property of the identification matrix is proposed, and the compensation effect is improved. This method has been verified by experiments on 1T2R parallel mechanism and can be extended to other similar parallel mechanisms.

• Publisher: Emerald Group Publishing Limited
• Subject: Accuracy / Algorithms / Attitudes / Calibration / Efficiency / Error analysis / Error compensation / Influence coefficient / Kinematics / Methods / Nutation / Optimization algorithms / Parameter estimation / Parameter identification / Position measurement / Principal components analysis / Robotics / Robots / Robustness / Sensitivity analysis / Trajectory measurement / Trajectory optimization