基于免疫遗传算法的冗余并联机构多目标优化  

Multi-objective optimization of redundant parallel mechanism based on immune genetic algorithm

作　　者：代小林 王鹏[1] 宫大为 DAI Xiaolin;WANG Peng;GONG Dawei(School of Mechanical and Electrical Engineering,University of Electronic Science and Technology of China,Chengdu 611731,China;Center for Robotics,University of Electronic Science and Technology of China,Chengdu 611731,China)

机构地区：[1]电子科技大学机械与电气工程学院,四川成都611731 [2]电子科技大学机器人中心,四川成都611731

出　　处：《哈尔滨工程大学学报》2018年第12期2033-2039,共7页Journal of Harbin Engineering University

基　　金：国家自然科学基金项目(51305066;61603076);四川省科技厅计划项目(2016GZ0198);中央高校基本科研业务费项目(ZYGX2016J200;ZYGX2016J116)

摘　　要：针对电动并联机构驱动能力不足的问题,提出用3条冗余支腿来平衡负载的结构。同时,考虑到实际工况下,速度、驱动力和功率峰值过高给机构带来的负面影响,使用免疫遗传算法对该并联机构的结构参数进行多目标优化。仿真结果表明:与典型的六自由度并联机构相比,优化后电动支腿的速度峰值下降13. 83%,驱动力峰值下降24. 50%,功率峰值下降45. 68%。该冗余结构及优化方案,能够有效提高电动并联机构的驱动能力,适用于重载运动模拟试验台。Considering the inefficiencies in the driving capability of electric parallel mechanism,a parallel manipulator with three redundant legs is proposed to balance gravity.In addition,an immune genetic algorithm is used to design the mechanism by multi-objective optimization to address the negative impact of the maximum velocity,driving force,and power in actual working conditions.The simulation result shows that compared with the typical six degree of freedom parallel mechanism,the maximum velocity,driving force,and power reduced by 13.83%,24.50%,and 45.68%,respectively,after optimization.The redundant structure and multi-objective optimization scheme can reduce the load of electric-driven legs,and it is suitable for the test bed of heavy load simulation.

关 键 词：并联机器人 冗余支撑 功率优化 速度优化 驱动力优化 免疫遗传算法 多目标优化 

分 类 号：TH112.1[机械工程—机械设计及理论]