| 引用本文: | 关新平, 唐英平, 段广仁.机械手臂基于神经网络动态补偿的自适应控制[J].控制理论与应用,2003,20(1):101~104.[点击复制] |
| GUAN Xin-ping, TANG Ying-gan, DUAN Guang-ren.Adaptive control for manipulator based on neural-network dynamic compensation[J].Control Theory and Technology,2003,20(1):101~104.[点击复制] |
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| 机械手臂基于神经网络动态补偿的自适应控制 |
| Adaptive control for manipulator based on neural-network dynamic compensation |
| 摘要点击 1650 全文点击 1839 投稿时间：2000-12-25 修订日期：2001-12-20 |
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| DOI编号 10.7641/j.issn.1000-8152.2003.1.023 |
| 2003,20(1):101-104 |
| 中文关键词 机械手臂 神经网络 自适应控制 |
| 英文关键词 manipulator neural networks adaptive control |
| 基金项目 国家自然科学基金(6950400260274023)资助项目 |
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| 中文摘要 |
| 研究了模型具有不确定性的机械手臂的跟踪控制问题.由于模型不确定性的存在,基于精确模型设计的控制律很难达到理想的控制效果.针对这种情况,在基于标称模型设计的控制律的基础上,采用神经网络来补偿模型的不确定性,由于神经网络存在逼近误差,因此在控制器设计时,引入了H∞ 鲁棒项,使得网络逼近误差达到指定的削弱水平并且跟踪误差渐近收敛到零,仿真结果表明了该方法的有效性. |
| 英文摘要 |
| The tracking control of manipulator with model uncertainties and external disturbance is studied. Due to the uncertainties, the controller design based on exact model is difficult to achieve. Thus a neural network is introduced to compensate the uncertainties based on the controller with exact model.Considering the existence of approximation error of the neural network, the H-infinity robust controller is introduced to reduce the approximation error to a prescribed level and the tracking error tends to zero. The effectiveness of this approach is demonstrated by the simulation examples. |
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