针对3自由度并联机器人,提出基于相关参数的动态参数辨识新方法。
A Methodology for Dynamic Parameters Identification of 3-DOF Parallel Robots in Terms of Relevant Parameters
- 从全模型出发,结合几何与对称性简化,聚焦关键相关参数。
- 实验验证表明,反向与正向动力学响应与实际测试高度吻合。
- 适合需要高精度动力学建模的并联机器人控制与仿真研究者。
机械系统动态参数的识别对于提升基于模型的控制性能和实现真实动态仿真至关重要。通常情况下,仅能辨识出一部分称为基础参数的变量,且部分参数因对机器人动力学贡献小,在测量噪声和建模误差下难以准确辨识。为此,本文提出一种针对全并联机器人、基于相关参数的动态参数辨识策略。该方法从完整动力学模型出发,通过考虑各构件几何特性及全并联机器人腿结构对称性进行简化,随后采用加权最小二乘法完成参数辨识。进一步引入统计分析,持续缩减模型直至满足物理可实现性条件。该策略在两种不同配置的实际3-DOF并联机器人上进行了实验验证,辨识模型的反向与正向动力学响应均与实验数据一致。为评估正向动力学性能,本文还提出了基于相关参数的正向动力学求解方法。
原文摘要 · Abstract (English)
The identification of dynamic parameters in mechanical systems is important for improving model-based control as well as for performing realistic dynamic simulations. Generally, when identification techniques are applied only a subset of so-called base parameters can be identified. More even, some of these parameters cannot be identified properly given that they have a small contribution to the robot dynamics and hence in the presence of noise in measurements and discrepancy in modeling, their quality of being identifiable decreases. For this reason, a strategy for dynamic parameter identification of fully parallel robots in terms of a subset called relevant parameters is put forward. The objective of the proposed methodology is to start from a full dynamic model, then simplification concerning the geometry of each link and, the symmetry due to legs of fully parallel robots, are carried out. After that, the identification is done by Weighted Least Squares. Then, with statistical considerations the model is reduced until the physical feasibility conditions are met. The application of the propose strategy has been experimentally tested on two difierent configurations of actual 3-DOF parallel robots. The response of the inverse and forward dynamics of the identified models agrees with experiments. In order to evaluate the forward dynamics response, an approach for obtaining the forward dynamics in terms of the relevant parameters is also proposed.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品;中文卡片由大模型生成,请以原文为准。