English 
刘凯

副教授 硕士生导师

招生学科专业:
机械工程 -- 【招收硕士研究生】 -- 机电学院
机械 -- 【招收硕士研究生】 -- 机电学院

性别:男

毕业院校:南京航空航天大学

学历:博士毕业

学位:工学博士学位

所在单位:机电学院

办公地点:明故宫校区A17-511

联系方式:13914708968 biomeasurement.nuaa.edu.cn

电子邮箱:

手机版

访问量:

最后更新时间:..

当前位置: 刘凯 >> 科学研究 >> 论文成果
Adaptive Multi-Objective Optimization of Bionic Shoulder Joint Based on Particle Swarm Optimization

点击次数:

所属单位:机电学院

发表刊物:J. Shanghai Jiaotong Univ. Sci.

摘要:To get the movement mode and driving mechanism similar to human shoulder joint, a six degrees of freedom (DOF) serial-parallel bionic shoulder joint mechanism driven by pneumatic muscle actuators (PMAs) was designed. However, the structural parameters of the shoulder joint will affect various performances of the mechanism. To obtain the optimal structure parameters, the particle swarm optimization (PSO) was used. Besides, the mathematical expressions of indexes of rotation ranges, maximum bearing torque, discrete dexterity and muscle shrinkage of the bionic shoulder joint were established respectively to represent its many-sided characteristics. And the multi-objective optimization problem was transformed into a single-objective optimization problem by using the weighted-sum method. The normalization method and adaptive-weight method were used to determine each optimization index’s weight coefficient; then the particle swarm optimization was used to optimize the integrated objective function of the bionic shoulder joint and the optimal solution was obtained. Compared with the average optimization generations and the optimal target values of many experiments, using adaptive-weight method to adjust weights of integrated objective function is better than using normalization method, which validates superiority of the adaptive-weight method. © 2018, Shanghai Jiaotong University and Springer-Verlag GmbH Germany, part of Springer Nature.

ISSN号:1007-1172

是否译文:

发表时间:2018-08-01

合写作者:Wu, Yang,Ge, Zhishang,王扬威,Xu, Jiaqi,陆永华,赵东标

通讯作者:刘凯

版权所有©2018- 南京航空航天大学·信息化处(信息化技术中心)