[1]李泽昕,徐凤,张孟玄,等.时变二次规划的高精度数值算法[J].华侨大学学报(自然科学版),2019,40(3):405-411.[doi:10.11830/ISSN.1000-5013.201807052]
 LI Zexin,XU Feng,ZHANG Mengxuan,et al.Numerical Algorithm With High Computational Precision for Time-Varying Quadratic Program[J].Journal of Huaqiao University(Natural Science),2019,40(3):405-411.[doi:10.11830/ISSN.1000-5013.201807052]
点击复制

时变二次规划的高精度数值算法()
分享到:

《华侨大学学报(自然科学版)》[ISSN:1000-5013/CN:35-1079/N]

卷:
第40卷
期数:
2019年第3期
页码:
405-411
栏目:
出版日期:
2019-05-20

文章信息/Info

Title:
Numerical Algorithm With High Computational Precision for Time-Varying Quadratic Program
文章编号:
1000-5013(2019)03-0405-07
作者:
李泽昕 徐凤 张孟玄 郭东生
华侨大学 信息科学与工程学院, 福建 厦门 361021
Author(s):
LI Zexin XU Feng ZHANG Mengxuan GUO Dongsheng
College of Information Science and Engineering, Huaqiao University, Xiamen 361021, China
关键词:
时变二次规划 数值算法 泰勒差分公式 机械臂 运动控制
Keywords:
time-varying quadratic program numerical algorithm Taylor difference formula robot manipulator motion control
分类号:
TP183
DOI:
10.11830/ISSN.1000-5013.201807052
文献标志码:
A
摘要:
提出一种用于求解时变二次规划问题的高精度数值算法.首先,给出求解时变二次规划问题的连续模型;然后,采用新型泰勒差分公式将连续模型离散,得到具有高计算精度的数值算法;最后,通过理论分析和仿真实验表明该数值算法的优越性和有效性,并将所提出的数值算法应用于一个五连杆机械臂的运动控制中.研究结果表明:所提算法的计算稳态误差与采样间隔τ具有O(τ4)的关系,该数值算法既可以有效地求解时变二次规划问题,又能有效地应用于机械臂的运动控制.
Abstract:
A high precision numerical algorithm is proposed to solve the problem of time-varying quadratic program. Firstly, the continuous-time model for time-varying quadratic program is given. Secondly, the numerical algorithm with a high computational precision is then derived by employing a new Taylor difference formula to discretize the above continuous-time model. Finally, the theoretical analysis and simulational experiments further indicate the superiority and effectiveness of the proposed numerical algorithm, and the proposed algorithm is applied to the motion control of a five-link robot manipulator. The results show that the calculated steady-state error of the proposed algorithm has a relationship of O(τ4)with the sampling interval τ, this numerical algorithm can both effectively solve the time-varying quadratic programming problem and apply to the motion control of the manipulator.

参考文献/References:

[1] NOCEDAL J,WRIGHT S J.Numerical optimization[M].New York:Springer-Verlag,1999.
[2] BOYD S,VANDENBERGHE L.Convex optimization[M].New York:Cambridge University,2004.
[3] 常雨芳,王豪,谢昊,等.采用矩阵建模方式的冷热电联供系统运行优化[J].华侨大学学报(自然科学版),2018,39(2):233-239.DOI:10.11830/ISSN.1000-5013.201703057.
[4] 沈国浪,童欣,李占福.应用GA-BP神经网络优化平摆复合振动筛的振动参数[J].华侨大学学报(自然科学版),2018,39(4):509-513.DOI:10.11830/ISSN.1000-5013.201803010.
[5] GUO Dongsheng,LIN Xinjie,SU Zhaozhu,et al.Design and analysis of two discrete-time ZD algorithms for time-varying nonlinear minimization[J].Numerical Algorithms,2018,77(1):23-36.DOI:10.1007/s11075-017-0302-4.
[6] BAI Zhongzhi,TAO Min.On preconditioned and relaxed AVMM methods for quadratic programming problems with equality constraints[J].Linear Algebra and its Applications,2017,516:264-285.DOI:10.1016/j.laa.2016.11.038.
[7] JIN Long,LI Shuai.Nonconvex function activated zeroing neural network models for dynamic quadratic programming subject to equality and inequality constraints[J].Neurocomputing,2017,267:107-113.DOI:10.1016/j.neucom.2017.05.017.
[8] LIAO Bolin,ZHANG Yunong,JIN Long.Taylor O(h3)discretization of ZNN models for dynamic equality-constrained quadratic programming with application to manipulators[J].IEEE Transactions on Neural Networks and Learning Systems,2016,27(2):225-237.DOI:10.1109/TNNLS.2015.2435014.
[9] 谢清,张雨浓,余晓填,等.面向冗余度机械臂QP问题求解的E47和94LVI数值算法[J].计算机工程与科学,2015,37(7):1405-1411.
[10] 刘德友,牛九肖.求解一类新的二次规划问题的时滞投影神经网络方法[J].华侨大学学报(自然科学版),2013,34(2):230-235.DOI:10.11830/ISSN.1000-5013.2013.02.0230.
[11] 田朝薇,宋海洲.求非凸二次约束二次规划全局解的凸规划方法[J].华侨大学学报(自然科学版),2011,32(4):458-462.DOI:10.11830/ISSN.1000-5013.2011.04.0458.
[12] ZHANG Yunong,WU Fangting,Xiao Zhengli,et al.Performance analysis of LVI-based PDNN applied to real-time solution of time-varying quadratic programming[C]//International Joint Conference on Neural Networks.Beijing:IEEE Press,2016:3155-3160.DOI:10.1109/IJCNN.2014.6889453.
[13] ZHANG Yunong,LI Zhan.Zhang neural network for online solution of time-varying convex quadratic program subject to time-varying linear-equality constraints[J].Physics Letters A,2009,373(18):1639-1643.
[14] MATHEWS J H,FINK F D.Numerical methods using MATLAB[M].New Jersey:Prentice Hall,2004.
[15] ZHANG Yunong,JIN Long,GUO Dongsheng,et al.Taylor-type 1-step-ahead numerical differentiation rule for first-order derivative approximation and ZNN discretization[J].Journal of Computational and Applied Mathematics,2015,273:29-40.DOI:10.1016/j.cam.2014.05.027.
[16] GUO Dongsheng,NIE Zhuoyun,YAN Laicheng.Novel discrete-time Zhang neural network for time-varying matrix inversion[J].IEEE Transactions on Systems Man and Cybernetics Systems,2017,47(8):2301-2310.DOI:10.1109/TSMC.2017.2656941.
[17] GUO Dongsheng,XU Feng,LI Zexin,et al.Design, verification, and application of new discrete-time recurrent neural network for dynamic nonlinear equations solving[J].IEEE Transactions on Industrial Informatics,2018,14(9):3936-3945.DOI:10.1109/TII.2017.2787729.
[18] GUO Dongsheng,YAN Laicheng,NIE Zhouyun.Design, analysis, and representation of novel five-step dtzd algorithm for time-varying nonlinear optimization[J].IEEE Transactions on Neural Networks and Learning Systems,2018,29((9):4248-4260.DOI:10.1109/TNNLS.2017.2761443.
[19] ZHANG Yunong,ZHANG Zhijun.Repetitive motion planning and control of redundant robot manipulators[M].New York:Springer-Verlag,2013.
[20] ZHANG Yunong,JIN Long.Robot manipulator redundancy resolution[M].Hoboken:Wiley,2017.
[21] JIN Long,LI Shuai,YU Jiguo,et al.Robot manipulator control using neural networks: A survey[J],Neurocomputing,2018,28:23-34.DOI:10.1016/j.neucom.2018.01.002.
[22] GRIFFITHS D F,HIGHAM D J.Numerical methods for ordinary differential equations: Initial value problems[M].England:Springer,2010.
[23] 余乐,李庆,郑力新,等.六自由度机械臂运动轨迹自动生成方法仿真与实现[J].华侨大学学报(自然科学版),2018,39(3):355-359.DOI:10.11830/ISSN.1000-5013.201706082.

备注/Memo

备注/Memo:
收稿日期: 2018-07-29
通信作者: 郭东生(1987-),男,副教授,博士,主要从事数值算法、神经网络和机器人的研究.E-mail:gdongsh@hqu.edu.cn.
基金项目: 国家自然科学基金资助项目(61603143); 福建省自然科学基金资助项目(2016J01307); 华侨大学中青年教师资助计划项目(ZQN-YX402); 高层次人才科研启动项目(15BS410); 华侨大学研究生科研创新能力培育计划资助项目(17013082041)
更新日期/Last Update: 2019-05-20