摘要
根据杆长约束条件,给出了求解3-RPR平面并联机构位置正解的无约束优化模型。针对标准粒子群算法容易陷入局部极值、进化后期收敛速度慢等缺点,提出了一种基于新的差异度评价指标的改进粒子群算法——自适应变异粒子群算法。采用自适应变异粒子群算法求并联机构位置正解中的优化问题。数值实例表明,改进粒子群算法能求出全部装配构型,且收敛速度较快、精度较高。
The unconstrained optimization model for the forward positional analysis of a 3-RPR planar parallel manipulator, which is based on the constrained length of the bars, is presented. The simple particle swarm optimization (SPSO) has some demerits, such as relapsing into local extremum and slow convergence velocity in the late evolutionary. The improved PSO, adaptive mutation PSO (AMPSO), based on the new difference index, is proposed to overcome the demerits of the SPSO. The adaptive mutation PSO (AMPSO) is given out to make the optimal problem for forward positional analysis of parallel mechanisms. Numerical results for the forward position analysis of 3-RPR planar parallel manipulator show that the AMPSO can solve to all assembly configurations, and possesses the performances of rather quick convergence speed and high precision.
出处
《机械传动》
CSCD
北大核心
2008年第2期39-42,共4页
Journal of Mechanical Transmission
基金
湖南省自然科学基金资助(2007fj3046)
关键词
3-RPR
平面并联机构
位置正解
粒子群算法
自适应变异
3-RPR planar parallel manipulator Forward positional analysis Particle swarm optimization Adaptive mutation
