• CN:11-2187/TH
  • ISSN:0577-6686

机械工程学报 ›› 2022, Vol. 58 ›› Issue (19): 229-241.doi: 10.3901/JME.2022.19.229

• 数字化设计与制造 • 上一篇    下一篇

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并联机构敏感性分析和多目标优化设计方法

杨超1, 叶伟2, 陈巧红3   

  1. 1. 嘉兴学院机电工程学院 嘉兴 314001;
    2. 浙江理工大学机械与自动控制学院 杭州 310018;
    3. 浙江理工大学信息学院 杭州 310018
  • 收稿日期:2021-12-06 修回日期:2022-07-14 出版日期:2022-10-05 发布日期:2023-01-05
  • 通讯作者: 陈巧红(通信作者),女,1978年出生,博士,副教授,研究生导师。主要研究方向为并联机器人。E-mail:chen_lisa@zstu.edu.cn
  • 作者简介:杨超,男,1982年出生,博士,讲师。主要研究方向为并联机器人运动学、刚度、动力学和多目标优化。E-mail:cyang@zjxu.edu.cn
  • 基金资助:
    国家自然科学基金(51775513)和浙江省自然科学基金(LY17E050028)资助项目。

Sensitivity Analysis and Multi-objective Optimization Design of Parallel Manipulators

YANG Chao1, YE Wei2, CHEN Qiaohong3   

  1. 1. College of Mechanical and Electrical Engineering, Jiaxing University, Jiaxing 314001;
    2. Mechatronic Institute, Zhejiang Sci-Tech University, Hangzhou 310018;
    3. School of Information, Zhejiang Sci-Tech University, Hangzhou 310018
  • Received:2021-12-06 Revised:2022-07-14 Online:2022-10-05 Published:2023-01-05

摘要: 为了解决并联机构全局性能指标高计算成本引起的敏感性分析和多目标优化设计困难,提出了一种结合多项式响应面模型、基于方差的敏感性分析方法和智能优化算法的高效计算方法。首先,确定并联机构的目标函数和设计参数,增加节点密度以提高目标函数的计算精度,基于拉丁超立方体抽样方法和最小二乘多项式拟合技术建立全局目标函数与设计参数之间的响应面解析映射模型,并结合基于方差的Sobol’敏感性分析方法得到对目标函数有重要影响的设计参数。然后,结合敏感性分析结果简化设计参数并建立并联机构的多目标优化设计模型,包括目标函数、约束函数和设计参数,结合响应面模型与智能优化算法开展并联机构多目标优化设计。最后,考虑规则工作空间体积、运动学性能和动力学性能指标为目标函数,以DELTA并联机构为例实现了本文提出的方法。优化前后的结果对比证明了算法的有效性。

关键词: 并联机构, 多目标优化设计, 性能指标, 敏感性分析

Abstract: An efficient calculation method combining multivariate regression response surface model (RSM), variance based sensitivity analysis method, and intelligent optimization algorithm to solve the high computation-intensive of sensitivity analysis and multi-objective optimization design of parallel manipulators (PMs) caused by the high computational cost of global performance indices (GPIs). First, establish objective functions and design parameters of PMs, increase the node density to improve the calculation accuracy of GPIs, establish the analytical RSM between the GPI and the design parameters using the Latin hypercube sampling method and least squares multivariate fitting technique, and then combine with the RSM and variance based Sobol’s sensitivity analysis method to obtain the important design parameters to the objective influence. Second, simplify design parameters based on the sensitivity analysis results and establish the multi-objective optimization design mathematical model of PMs, including objective functions, design parameters and constraint functions. Combine with RSMs and intelligent optimization algorithm to carry out multi-objective optimization design of PMs. Finally, considering the regular workspace volume, global kinematic and dynamic performance indices as objective functions, the DELTA PM is taken as an example to implement the proposed method. The comparison of the results before and after optimization proves the effectiveness of the proposed method.

Key words: parallel manipulator, multi-objective optimization design, performance index, sensitivity analysis

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