蜂群粒子群混合算法在机械手参数优化中的应用研究

doi:10.16182/j.issn1004731x.joss.201801013

系统仿真学报 ›› 2018, Vol. 30 ›› Issue (1): 105-113.doi: 10.16182/j.issn1004731x.joss.201801013

蜂群粒子群混合算法在机械手参数优化中的应用研究

宫赤坤¹, 孙英慧¹, 袁立鹏^2,3

1.上海理工大学机械工程学院,上海 200093;
2.常州恐龙园股份有限公司,常州 213022;
3.哈尔滨工业大学机电工程学院,哈尔滨 150001

收稿日期:2015-12-22 发布日期:2019-01-02
作者简介:宫赤坤(1968-),男,辽宁大连,博士,副教授,研究方向为机器人学;孙英慧(1990-),男,山东莱芜,硕士生,研究方向为工业机器人;袁立鹏(1976-),男,内蒙古呼和浩特,博士,副教授,研究方向为液压伺服控制等。
基金资助:
国家科技支撑计划(2013BAH57F00)

Study on Application of Hybrid Optimization Algorithm in Parameters Optimization of Manipulator

Gong Chikun¹, Sun Yinghui¹, Yuan Lipeng^2,3

1.School of Mechanical Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China;
2.Changzhou Dinosaur Park Co., Ltd, Changzhou 213022, China;
3.School of Mechanical and Electrical Engineering, Harbin Institute of Technology, Harbin 150001, China

Received:2015-12-22 Published:2019-01-02

摘要/Abstract

摘要： 工业机械手进行精密加工时,尽可能在全姿态工作空间内部完成。为了得到紧凑的结构,同时满足加工点都为全姿态点,提出了一种新的蜂群粒子群混合优化算法。建立机械手全姿态空间的结构模型,引入粒子群中全局最优粒子和惯性权重两个参数,通过中间值进行分类,差异权衡惯性权重,增强寻优能力。经验证,该算法搜索能力更强,寻优精度更高。对结构优化模型进行参数辨识,结果表明,在保持原来全姿态空间大小基本不变的情况下得到了结构紧凑、质量最优的杆长参数,从而验证了所提算法的有效性、可行性。

关键词: 工业机械手, 全姿态工作空间, 杆长参数, 中间值, 惯性权重

Abstract: When the industrial robot carries on the precise processing, it is possible to finish in the work space of the whole attitude. In order to obtain the compact structure and meet the processing point, a new hybrid optimization algorithm is proposed. The structure model of the robot is established, and the global optimal particle and inertia weight of the particle swarm is introduced. The two parameters are classified by the intermediate value. The dynamic changes of the search medium and the optimization ability are enhanced. After verification, the algorithm has better search ability and higher accuracy. Finally, parameter identification of the structural optimization model, the results show that the obtained structure is compact and the quality of the rod length parameter is better while keeping the same size of the original quasi total attitude, Thereby, the proposed algorithm is effective and practical.

Key words: industrial robot, quasi full pose workspace, rod length parameter, intermediate value, inertia weight

中图分类号:

TP24

宫赤坤, 孙英慧, 袁立鹏. 蜂群粒子群混合算法在机械手参数优化中的应用研究[J]. 系统仿真学报, 2018, 30(1): 105-113.

Gong Chikun, Sun Yinghui, Yuan Lipeng. Study on Application of Hybrid Optimization Algorithm in Parameters Optimization of Manipulator[J]. Journal of System Simulation, 2018, 30(1): 105-113.

参考文献

[1] Nicolae Plitea, Andras Szilaghyi, Doina Pisla.Kinematic analysis of a new 5-DOF modular parallel robot for brachytherapy[J]. Robotics and Computer-Integrated Manufacturing(S0736-5845), 2015, 31(2): 70-80.
[2] 夏伯雄, 杜军. 基于复杂零件五轴加工系统的可重构机器人建模与试验[J]. 中国机械工程, 2014, 25(9): 1208-1213.Xia Boxiong, Du Jun. The modeling and experiment of reconfigurable robot based on the five-axis machining system of complex parts[J]. China Mechanical Engineering, 2014, 25(9): 1208-1213.
[3] 常定勇, 方跃法. 多输出3D打印冗余并联机器人的设计与分析[J]. 中国机械工程, 2015, 26(12): 1595-1602. Chang Dingyong, Fang Yuefa. Multi-output 3D printing redundant parallel robot design and analysis[J]. China Mechanical Engineering, 2015, 26(12): 1595-1602.
[4] S Seriani, P Gallina, A Gasparetto.A Performance Index for Planar Repetitive Workspace Robots[J]. Journal of Mechanisms and Robotics(S1942-4302), 2014, 6(3): 1942.
[5] Ericka Madrid, Marco Ceccarelli.Numerical solution for designing telescopic manipulators with prescribed workspace points[J]. Robotics and Computer-Integrated Manufacturing(S0736-5845), 2014, 30(2): 201-205.
[6] S Seriani, M Seriani, P Gallina.Workspace optimization for a planar cable-suspended direct-driven robot[J]. Robotics and Computer-Integrated Manufacturing (S0736-5845), 2015, 34(2): 1-7.
[7] 马香峰. 机器人机构学[M]. 北京: 机械工业出版社, 1991. Ma Xiangfeng. Robot Mechanism[M]. Beijing: Machinery Industry Press, 1991.
[8] D Karaboga, B Basturk.On the performance of artificial bee colony (ABC) algorithm[J]. Applied Soft Computing (S1568-4946), 2008, 8(7): 687-697.
[9] Alatas B.Chaotic bee colony algorithms for global numerical optimization[J]. Expert Systems with Applications(S0957-4174), 2010, 37(8): 5682-5687.
[10] 李鑫滨, 陈云强, 张淑清. 基于改进ABC算法优化的LSSVM多分类器组机械故障诊断模型[J]. 中国机械工程, 2013, 24(16): 2157-2164. Li Xinbin, Chen Yunqiang, Zhang Shuqing. Mechanical fault diagnosis model based on ABC algorithm optimized multiple LSSVM classifier group[J]. China Mechanical Engineering, 2013, 24(16): 2157-2164.
[11] 高卫峰, 刘三阳, 黄玲玲. 受启发的人工蜂群算法在全局优化问题中的应用[J]. 电子学报, 2012, 40(12): 32396-32403. GAO Wei-feng, LIU San-yang, HUANG Ling-ling. Inspired Artificial Bee Colony Alogrithm for Global Optimization Problems[J]. Acta Eletronica Sinica, 2012, 40(12): 32396-32403.
[12] Kennedy J, Eberhart R.Particle swarm optimization[C]// Proceedings of IEEE International Conference on Neural Networks. Piscataway, NJ, USA: IEEE, 1995: 1942-1948.
[13] EI-Abd M.A hybrid ABC-SPSO algorithm for continuous function optimization[C]//IEEE Symposium on Swarm Intelligence(SIS), Paris: IEEE Press, 2011:1-6.
[14] Zhu Guopu, Sam Kwong.Gbest-guided artificial bee colony algorithm for numerical function optimization[J]. Applied Mathematics and Computation(S0096-3003), 2010, 217(6): 3166-3173.
[15] 匡芳君, 金忠, 徐蔚鸿, 等. Tent 混沌人工蜂群与粒子群混合算法[J]. 控制与决策, 2015, 30(5): 839-847. KUANG Fangjun, JIN Zhong, XU Weihong, et al. Hybridiza algorithm of Tent chaos artificial bee colony particle swarm optimization[J]. Control and Decision, 2015, 30(5): 839-847.

蜂群粒子群混合算法在机械手参数优化中的应用研究

Study on Application of Hybrid Optimization Algorithm in Parameters Optimization of Manipulator

PDF (PC)

可视化

被引次数

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 4

编辑推荐

Metrics

本文评价

[1]	邵良杉, 王振, 李昌明. 基于模拟退火与改进粒子群的矿井通风优化算法[J]. 系统仿真学报, 2021, 33(9): 2085-2094.
[2]	魏腾飞, 潘庭龙. 基于改进PSO优化LSTM网络的短期电力负荷预测[J]. 系统仿真学报, 2021, 33(8): 1866-1874.
[3]	刘景森, 刘晓珍, 李煜. 具有动态步长和发现概率的布谷鸟搜索算法[J]. 系统仿真学报, 2020, 32(2): 289-298.
[4]	曾艳阳, 冯云霞, 赵文涛. 基于logistic映射的自适应变尺度混沌粒子群算法[J]. 系统仿真学报, 2017, 29(10): 2241-2246.