Please wait a minute...
J4  2010, Vol. 44 Issue (7): 1394-1399    DOI: 10.3785/j.issn.1008-973X.2010.07.029
自动化技术     
机械臂协调操作柔性负载鲁棒神经网络控制
唐志国1,2, 李元春2, 刘木林1,2
1.吉林大学 汽车动态模拟国家重点实验室,吉林 长春 130022;2.吉林大学 通信工程学院,吉林 长春 130022
Robust neural network control of dual-manipulator cooperative
system handling flexible payload
TANG Zhi-guo1,2, LI Yuan-chun2, LIU Mu-lin1,2
1.State Key Laboratory of Automobile Dynamic Simulation, Jilin University, Changchun 130022, China;
2. College of Communication Engineering, Jilin University, Changchun 130022, China
 全文: PDF  HTML
摘要:

针对多变量刚柔耦合的双机械臂协调操作柔性负载系统,基于奇异摄动理论研究该系统有限元模型的分解以及轨迹跟踪控制问题.考虑动力学模型的复杂性,通过双时标变换将协调系统分解成表征系统大范围刚性运动的慢变子系统和表征系统弹性振动的快变子系统.基于反演思想在慢变子系统中设计鲁棒神经网络控制策略,实现系统轨迹跟踪性能;针对快变子系统,设计鲁棒最优控制策略抑制系统的弹性振动.仿真研究结果表明,该控制策略增强了系统的跟踪性能和鲁棒性.

Abstract:

Aimed at the multivariable rigidflexible coupling system of dualmanipulator cooperative system handling a flexible payload, the decomposition and the trajectory tracking control of finite element modeling for the system were conducted based on the singular perturbation theory. Considering the complexity of dynamic model, the model was divided into two subsystems which included a slow subsystem describing the large rigid motion and a fast subsystem expressing the elastic vibration by the dualtime scale transform. A robust neural network controller was designed based on the idea of backstepping in the slow subsystem in order to complete the system trajectory tracking performance. For the fast subsystem, a robust optimal controller was presented to suppress the elastic vibration of the system. Simulation results show that the controller can strengthen the tracing ability and the robustness of the system.

出版日期: 2010-07-01
:  TP 273  
基金资助:

国家自然科学基金资助项目(60974010,60674091).

通讯作者: 李元春,男,教授,博导.     E-mail: yuanchun@jlu.edu.cn
作者简介: 唐志国(1984—),男,黑龙江哈尔滨人,博士生,从事机械臂协调控制的研究.E-mail:tangning20020321@yahoo.cn
服务  
把本文推荐给朋友
加入引用管理器
E-mail Alert
RSS
作者相关文章  

引用本文:

唐志国, 李元春, 刘木林. 机械臂协调操作柔性负载鲁棒神经网络控制[J]. J4, 2010, 44(7): 1394-1399.

TANG Zhi-Guo, LI Yuan-Chun, LIU Mu-Lin. Robust neural network control of dual-manipulator cooperative
system handling flexible payload. J4, 2010, 44(7): 1394-1399.

链接本文:

http://www.zjujournals.com/eng/CN/10.3785/j.issn.1008-973X.2010.07.029        http://www.zjujournals.com/eng/CN/Y2010/V44/I7/1394

[1] KOSUGE K, HASHIMOTO S, YOSHIDA H. Humanrobots collaboration system for flexible object handling [C]∥IEEE International Conference on Robotics and Automation. Leuven, Belgium: IEEE, 1998: 18411846.
[2] ZHENG Y F, CHEN M Z. Trajectory planning for two robot manipulators to deform flexible beams [C]∥Proceedings of IEEE International Conference on Robotics and Automation. Atlanta, USA: IEEE, 1993: 10191024.
[3] JAMES K M, JERRY G L I. Robotic fixtureless assembly of sheet metal parts using dynamic finite element models: modeling and simulation [C]∥Proceedings of IEEE International Conference on Robotics and Automation. Nagoya, Japan: IEEE, 1995: 2530 2537.
[4] JAMES K M, JERRY G L. Dynamic modeling and control of a multirobot system for assembly of flexible payloads with application to automotive body assembly [J]. Journal of Robotic Systems, 1996, 13(12): 817836.
[5] SUN Dong, LIU Yunhui. Stabilizing a flexible beam handled by two manipulators via PD feedback [J]. IEEE Transactions on Automatic Control, 2000, 45(11): 21592164.
[6] SUN Dong, LIU Yunhui. Position and force tracking of a twomanipulator system manipulating a flexible beam [J]. Journal of Robotic Systems, 2001, 18(4): 197212.
[7] SUN Dong, LIU Yunhui. Position and force tracking of a twomanipulator system manipulating a flexible beam payload [C]∥ Proceedings of IEEE International Conference on Robotics and Automation. Seoul: IEEE, 2001: 34833488.
[8] AMER S Y, JAMIL A, HSIA T C. Modeling and control of two manipulators handling a flexible object [J]. Journal of the Franklin Institute, 2006, 344(5): 349361.
[9] ZHANG Peng, LI Yuanchun. Position/force control of two manipulators handling a flexible payload based on finiteelement model [C]∥Proceedings of IEEE International Conference on Robotics and Biomimetics. Sanya: IEEE, 2007: 2178 2182.
[10] ZHANG Peng, LI Yuanchun. Simulations and trajectory tracking of two manipulators manipulating a flexible payload [C]∥ International Conference on Robotics, Automation and Mechatronics. Chengdu: IEEE, 2008: 7277.
[11] TANG Zhiguo, LI Yuanchun. Modeling and control of two manipulators handling a flexible payload based on singular perturbation [C]∥The 2nd IEEE International Conference on Advanced Computer Control. Shenyang: IEEE, 2010: 558562.
[12] 许可康.控制系统中的奇异摄动[M].北京:科学出版社,1986: 2331.
[13] FRANK L L, AYDIN Y, KAI L. Multilayer neuralnet robot controller with guaranteed tracking performance [J]. IEEE Transactions on Neural Networks, 1996, 7(2): 388399.

[1] 程森林,李雷,朱保卫,柴毅. WSN定位中的RSSI概率质心计算方法[J]. J4, 2014, 48(1): 100-104.
[2] 方强, 陈利鹏, 费少华, 梁青霄, 李卫平, 赵金锋. 定位器模型参考自适应控制系统设计[J]. J4, 2013, 47(12): 2234-2242.
[3] 罗继亮, 王飞,邵辉,赵良煦. 基于约束转换的Petri网最优监控器设计[J]. J4, 2013, 47(11): 2051-2056.
[4] 任雯, 胥布工. 基于FI-SNAPID算法的经编机多速电子送经系统开发[J]. J4, 2013, 47(10): 1712-1721.
[5] 李奇安, 金鑫. 对角CARIMA模型多变量广义预测近似解耦控制[J]. J4, 2013, 47(10): 1764-1769.
[6] 叶凌云,陈波,张建,宋开臣. 基于最少拍无波纹算法的高精度动态标准源反馈控制[J]. J4, 2013, 47(9): 1554-1558.
[7] 孟德远,陶国良,钱鹏飞,班伟. 气动力伺服系统的自适应鲁棒控制[J]. J4, 2013, 47(9): 1611-1619.
[8] 叶凌箭,马修水. 基于软测量技术的化工过程优化控制策略[J]. J4, 2013, 47(7): 1253-1257.
[9] 黄晓烁,何衍,蒋静坪. 基于互联网无刷直流电机传动系统的控制策略[J]. J4, 2013, 47(5): 831-836.
[10] 贺乃宝, 高倩, 徐启华, 姜长生. 基于自适应观测器的飞行器抗干扰控制[J]. J4, 2013, 47(4): 650-655.
[11] 朱予辰,冯冬芹,褚健. 基于EPA的块数据流通信调度与控制[J]. J4, 2012, 46(11): 2097-2102.
[12] 朱康武, 顾临怡, 马新军, 胥本涛. 水下运载器多变量鲁棒输出反馈控制方法[J]. J4, 2012, 46(8): 1397-1406.
[13] 刘志鹏, 颜文俊. 预粉磨系统的智能建模与复合控制[J]. J4, 2012, 46(8): 1506-1511.
[14] 费少华,方强,孟祥磊,柯映林. 基于压脚位移补偿的机器人制孔锪窝深度控制[J]. J4, 2012, 46(7): 1157-1161.
[15] 于晓明, 蒋静坪. 基于神经网络延时预测的自适应网络控制系统[J]. J4, 2012, 46(2): 194-198.