基于遗传算法的冗余任务并联机器人驱动优化  

Drive Optimization of Parallel Robot under Redundant Tasks Based on Genetic Algorithm

作　　者：刘玮[1] 常思勤[1] 

机构地区：[1]南京理工大学机械工程学院,南京210094

出　　处：《农业机械学报》2012年第4期221-224,220,共5页Transactions of the Chinese Society for Agricultural Machinery

基　　金：江苏省科技支撑计划资助项目(BE2008133)

摘　　要：以六棱锥式并联机器人为研究对象,采用拉格朗日法建立机构动力学模型,结合直线电动机设计原理,获得驱动电流与任务轨迹之间变化的对应关系。基于遗传算法以瞬时动能最小为优化目标对电动机驱动力进行优化,优化后能耗较非冗余任务能耗降低了47.6%。进行了样机冗余任务轨迹实验,实验结果表明电流变化与仿真结果吻合,验证了优化方法的可行性和合理性。A six pyramid parallel robot was taken as the object,and the dynamic model of the robot was established by using the Lagrange method.The relationship between the drive current and tasks trajectory was analyzed combined with the design principle of linear motor.With the goal of minimum instantaneous kinetic energy,motor drive was optimized based on genetic algorithm.Energy consumption optimized was reduced by 47.6% compared with non redundant tasks.The experiment of redundant track tasks was carried out.The experimental results showed that the current change was in good agreement with the simulation results,and the feasibility and rationality of this optimization method was verified.

关 键 词：并联机器人 动力学 遗传算法 冗余优化 

分 类 号：TH112[机械工程—机械设计及理论] TP242[自动化与计算机技术—检测技术与自动化装置]