基于Metropolis遗传算法的并联机器人结构优化设计

Structural Design Optimization of Parallel Manipulator Based on Metropolis Genetic Algorithm

  • 摘要: 以六自由度Stewart并联机器人的灵巧度为目标函数,以设计空间、每条支腿的最大最小长度之比和虎克铰、球铰的极限摆角为约束条件建立了结构优化模型.将模拟退火算法中的Metropolis准则引入到实值编码遗传算法的选择操作中,产生了Metropolis遗传算法,采用该算法进行了并联机器人结构优化问题的求解.通过与采用标准遗传算法得出的结果比较,证实了Metropolis遗传算法在并联机器人结构优化设计中的有效性和优越性.

     

    Abstract: A structural optimization model is developed,in which the kinematic dexterity of a 6 DOF Stewart paralllel manipulator is considered as the objective function, and the design space,the ratio of the maximum to minimum length of each leg,the limit angles of universal and spherical joints are taken as constraints.The Metropolis genetic algorithm,in which the Metropolis criterion of simulated annealing algorithm are incorporated in the selection operations of real-coded genetic algorithm,is applied to the structural design optimization of parallel manipulator.Results obtained by canonical and Metropolis genetic algorithms are compared,proving the validity and advantage of Metropolis genetic algorithm for structural design optimization of parallel manipulator.

     

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