6-SPS并联机构位置正解的改进粒子群算法

Improved particle swarm optimization algorithm for forward positional analysis of 6-SPS parallel manipulators

对6-SPS并联机构的运动学正解进行研究,得出6-SPS并联机构运动学正解的数学模型为一个非线性方程组。将所得的非线性方程组转化为无约束优化问题,并使用粒子群算法对其求解。针对并联机构运动学正解问题的多解性,提出改进的共享适应度粒子群算法。最后,用一个实例证明该方法是行之有效的。

Addresses the direct kinematics of 6-SPS parallel mechanism, the mathematics model of the direct kinematics of 6-SPS parallel mechanism which is nonlinear equations is presented. The nonlinear equations model could be translated into unconstrained optimization. And then,the Particle Swarm Optimization （PSO）algorithm is used for solving the optimization problem. Aimed at all forward positional solutions of parallel mechanisms were hard to obtain, directed towards this weakness, the improved PSO, Sharing Fitness Particle Swarm Optimization（SFPSO） algorithm was proposed. At last, a direct kinematics of one 6-SPS parallel platform was solved successfully by this algorithm.