Parameter optimization of heavy-load parallel manipulator by introducing stiffness distribution evaluation index

被引:32
|
作者
Wang, Hao [1 ]
Zhang, Linsong [1 ]
Chen, Genliang [1 ]
Huang, Shunzhou [2 ]
机构
[1] Shanghai Jiao Tong Univ, Sch Mech Engn, Shanghai Key Lab Digital Manufacture Thin Walled, State Key Lab Mech Syst & Vibrat, Shanghai 200240, Peoples R China
[2] Shanghai Aerosp Equipment Manufacturer, Shanghai 200245, Peoples R China
基金
美国国家科学基金会;
关键词
Parameter optimization; Stiffness distribution index; KES analysis; PSO algorithm; Parallel manipulator; DIMENSIONAL SYNTHESIS; PARTICLE SWARM; OPTIMAL-DESIGN; ROBOT;
D O I
10.1016/j.mechmachtheory.2016.10.011
中图分类号
TH [机械、仪表工业];
学科分类号
0802 ;
摘要
Aiming at the heavy-load parallel robotic manipulators, other than classic sequential 'topology dimension-structure' parameter design methodology, this paper proposes a new way to optimize dimension and structure parameters(1) simultaneously. To deal with the low-speed but heavy load working environment, a new type of stiffness performance evaluation index is introduced based on kineto-elastic statics (KES) analysis. This stiffness distribution index, mainly focuses on the stiffness distribution among all parts in the manipulator, along with two other dynamic performance indices and some dimensional constraints, formulate a multi-objective optimization model. Then the particle swarm optimization (PSO) algorithm is introduced to search for the optimum parameters. This method is applied on a widely used TRICEPT parallel manipulator, the dynamic performances before and after optimization are compared to verify this effectiveness of this method.
引用
收藏
页码:244 / 259
页数:16
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