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凿岩机器人钻臂定位误差补偿控制交叉精英反向粒子群优化算法

黄开启 魏文彬 陈荣华 丁问司

黄开启, 魏文彬, 陈荣华, 丁问司. 凿岩机器人钻臂定位误差补偿控制交叉精英反向粒子群优化算法[J]. 机械科学与技术, 2018, 37(7): 1005-1012. doi: 10.13433/j.cnki.1003-8728.2018.0702
引用本文: 黄开启, 魏文彬, 陈荣华, 丁问司. 凿岩机器人钻臂定位误差补偿控制交叉精英反向粒子群优化算法[J]. 机械科学与技术, 2018, 37(7): 1005-1012. doi: 10.13433/j.cnki.1003-8728.2018.0702
Huang Kaiqi, Wei Wenbin, Chen Ronghua, Ding Wensi. CEOPSO Algorithm for Positioning Error Compensation Control of Rock Drilling Robotic Drilling Arm[J]. Mechanical Science and Technology for Aerospace Engineering, 2018, 37(7): 1005-1012. doi: 10.13433/j.cnki.1003-8728.2018.0702
Citation: Huang Kaiqi, Wei Wenbin, Chen Ronghua, Ding Wensi. CEOPSO Algorithm for Positioning Error Compensation Control of Rock Drilling Robotic Drilling Arm[J]. Mechanical Science and Technology for Aerospace Engineering, 2018, 37(7): 1005-1012. doi: 10.13433/j.cnki.1003-8728.2018.0702

凿岩机器人钻臂定位误差补偿控制交叉精英反向粒子群优化算法

doi: 10.13433/j.cnki.1003-8728.2018.0702
基金项目: 

国家自然科学基金项目(11272122)、广东省部产学研重大项目(2012A090300011)及江西省科技厅对外合作重点项目(20123BBE50085)资助

详细信息
    作者简介:

    黄开启(1969-),教授,博士,研究方向为矿山智能开采装备、车辆动力学与控制,kaiqi.huang@163.com

CEOPSO Algorithm for Positioning Error Compensation Control of Rock Drilling Robotic Drilling Arm

  • 摘要: 为提高凿岩机器人钻臂末端(钎头)的定位精度,在利用粒子群优化(PSO)算法对关节变量误差进行补偿时,存在收敛速度慢、容易过早陷入局部最优解等问题,为此,提出一种交叉精英反向粒子群优化算法(CEOPSO)并给出算法流程。针对影响误差的两个主要因素,采用五参数D-H方法建立钻臂的参数误差模型,在形变关节后引入一个虚拟关节,推导出钻臂的形变误差模型。将交叉算子引入到EOPSO算法中,同时进行自适应惯性权重和交叉概率参数控制,不仅维持了粒子个体与最优解之间的信息交换,而且增加了粒子个体之间的信息交换。对比仿真结果表明,在误差补偿控制过程中,CEOPSO算法具有更优越的最优关节补偿值搜索收敛速度和求解稳定性,提高了凿岩机器人钻臂的定位控制性能。
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出版历程
  • 收稿日期:  2017-08-10
  • 刊出日期:  2018-07-05

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