Multi-objective optimization design of parallel manipulators using a neural network and principal component analysis

IF 1 4区工程技术 Q4 ENGINEERING, MECHANICAL

Mechanical Sciences Pub Date : 2023-09-06 DOI:10.5194/ms-14-361-2023

Chao Yang, Peijiao Li, Yang Wang, Wei Ye, Tianze Sun, Fengli Huang, Hui Zhang

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Abstract

Abstract. In this work, a multi-objective optimization design method is proposed based on principal component analysis (PCA) and a neural network to obtain a mechanism's optimal comprehensive performance. First, multi-objective optimization mathematical modeling, including design parameters, objective functions, and constraint functions, is established. Second, the sample data are obtained through the design of the experiment (DOE) and are then standardized to eliminate the adverse effects of a non-uniform dimension of objective functions. Third, the first k principal components are established for p performance indices (k

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基于神经网络和主成分分析的并联机器人多目标优化设计

摘要提出了一种基于主成分分析(PCA)和神经网络的多目标优化设计方法，以获得机构的最优综合性能。首先，建立包括设计参数、目标函数和约束函数在内的多目标优化数学模型;其次，通过实验设计(DOE)获得样本数据，然后进行标准化，以消除目标函数维数不均匀的不利影响。第三，利用基于方差的主成分分析法对p个绩效指标(k

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来源期刊

Mechanical Sciences ENGINEERING, MECHANICAL-

CiteScore

2.20

自引率

7.10%

发文量

审稿时长

29 weeks

期刊介绍： The journal Mechanical Sciences (MS) is an international forum for the dissemination of original contributions in the field of theoretical and applied mechanics. Its main ambition is to provide a platform for young researchers to build up a portfolio of high-quality peer-reviewed journal articles. To this end we employ an open-access publication model with moderate page charges, aiming for fast publication and great citation opportunities. A large board of reputable editors makes this possible. The journal will also publish special issues dealing with the current state of the art and future research directions in mechanical sciences. While in-depth research articles are preferred, review articles and short communications will also be considered. We intend and believe to provide a means of publication which complements established journals in the field.

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