| 基于模糊神经网络的机器人关节驱动补偿控制器 |
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| 引用本文： | 刘彦忠,戴学丰,刘艳菊.基于模糊神经网络的机器人关节驱动补偿控制器[J].微计算机信息,2006,22(2):215-217. |
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| 作者姓名： | 刘彦忠 戴学丰 刘艳菊 |
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| 作者单位： | 161006,齐齐哈尔大学计算机与控制学院 |
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| 基金项目： | 黑龙江省教育厅科学技术研究项目 |
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| 摘 要： | 本文提出了一种模糊神经网络控制器,该控制器用于工业机器人关节驱动的位置控制,克服了传统PID很难达到对非线性以及不确定因素的控制效果和简单模糊控制不能完全消除稳态误差的缺点,通过神经网络对模糊规则的学习优化,提高了机器人关节末端位置精度,具有较好控制效果。
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| 关 键 词： | 模糊神经网络 传统PID控制 补偿控制 |
| 文章编号： | 1008-0570(2006)01-2-0215-03 |
| 修稿时间： | 2005年12月12 |
Compensation Controller for Joint Actuation of Robot Manipulators Based on Fuzzy-Neural Network |
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| Liu,Yanzhong,Dai,Xuefeng,Liu,Yanjv.Compensation Controller for Joint Actuation of Robot Manipulators Based on Fuzzy-Neural Network[J].Control & Automation,2006,22(2):215-217. |
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| Authors: | Liu Yanzhong Dai Xuefeng Liu Yanjv |
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| Abstract: | A kind of fuzzy-neural network control is proposed in the paper. It is used to joint actuation for robotic manipulators position servo system. It overcomes some defects of traditional PID control which is difficult to control nonlinear and uncertainties event and simply fuzzy control which can not remove steady error thoroughly. The control accuracy of position was improved by learning and optimizing fuzzy rules. The simulation and experimental results show that this method improves the control performance of system and has preferable effects. |
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| Keywords: | fuzzy-neural network traditional PID control Compensation control |
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