| Adaptive Control of Flexible Redundant Manipulators Using Neural Networks |
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| 作者姓名： | 宋轶民 李建新 王世宇 刘建平 |
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| 作者单位： | School of Mechanical Engineering Tianjin University，School of Mechanical Engineering Tianjin University，School of Mechanical Engineering Tianjin University，School of Mechanical Engineering Tianjin University，Tianjin 300072 China Tianjin 300072 China Tianjin 300072 China Tianjin 300072 China |
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| 基金项目： | Supported by National Natural Science Foundation of China(No.59975001 and 50205019). |
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| 摘 要： | Nowadays, the operation tasks and environmentof robotic manipulators have become more and moresophisticated, which requires that robotic manipula-tors possess more and more degrees of freedom(DOF) to offer greater dexterity and versatility. Thekinematic redundancy occurs when the DOF of a ma-nipulator is more than the minimum numberdemanded for executing a given task. The operationalperformance of manipulators may be greatly enhancedby utilizing the kinematic redundancy such as singu-larity …
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| 关 键 词： | 柔性制造 运动学冗余 主动振动控制 神经网络 自适应控制 |
| 收稿时间： | 2006-07-07 |
Adaptive Control of Flexible Redundant Manipulators Using Neural Networks |
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| SONG Yimin,LI Jianxin,WANG Shiyu,LIU Jianping.Adaptive Control of Flexible Redundant Manipulators Using Neural Networks[J].Transactions of Tianjin University,2006,12(6):429-433. |
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| Authors: | SONG Yimin LI Jianxin WANG Shiyu LIU Jianping |
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| Abstract: | An investigation on the neural networks based active vibration control of flexible redundant manipulators was conducted. The smart links of the manipulator were synthesized with the flexible links to which were attached piezoceramic actuators and strain gauge sensors. A nonlinear adaptive control strategy named neural networks based indirect adaptive control (NNIAC) was employed to improve the dynamic performance of the manipulator. The mathematical model of the 4-layered dynamic recurrent neural networks (DRNN) was introduced. The neuro-identifier and the neuro-controller featuring the DRNN topology were designed off line so as to enhance the initial robustness of the NNIAC. By adjusting the neuro-identifier and the neuro-controller alternatively, the manipulator was controlled on line for achieving the desired dynamic performance. Finally, a planar 3R redundant manipulator with one smart link was utilized as an illustrative example. The simulation results proved the validity of the control strategy. |
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| Keywords: | flexible manipulators kinematic redundancy active vibration control neural networks adaptive control |
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