| 神经网络在伺服系统中进行摩擦力补偿的方法 |
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| 引用本文： | 王欣峰[,] 高伟.神经网络在伺服系统中进行摩擦力补偿的方法[J].科学技术与工程,2005,5(19):1321-1323. |
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| 作者姓名： | 王欣峰[ ] 高伟 |
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| 作者单位： | 中国科学院西安光学精密机械研究所,西安 710068;中科院研究生院,北京 100048;中国科学院西安光学精密机械研究所,西安 710068 |
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| 摘 要： | 由于非线性摩擦力的存在,很难用传统的方法对其进行建模。首先讨论了摩擦力及其描述方法,在通过用神经网络对被控对象进行建模的基础之上,利用自适应逆模型神经网络控制器并联PID反馈控制器对控制对象中的摩擦力进行了补偿,并通过一直流伺服系统的仿真试验,验证了该方法是可行的。
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| 关 键 词： | 伺服系统 神经网络 摩擦力补偿 自适应逆模型 |
| 文章编号： | 1671-1815(2005)19-1321-03 |
| 收稿时间： | 06 6 2005 12:00AM |
| 修稿时间： | 2005年6月6日 |
The Friction Compensation Method in Servo System Using ANN |
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| WANG Xinfeng,GAO Wei Xi''an Institute of Optics and Precision Mechanism of CAS,Xi''an,Graduate School of China Association of Science,Beijing.The Friction Compensation Method in Servo System Using ANN[J].Science Technology and Engineering,2005,5(19):1321-1323. |
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| Authors: | WANG Xinfeng GAO Wei Xi'an Institute of Optics and Precision Mechanism of CAS Xi'an Graduate School of China Association of Science Beijing |
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| Institution: | WANG Xinfeng,GAO Wei Xi'an Institute of Optics and Precision Mechanism of CAS,Xi'an,710068, Graduate School of China Association of Science,Beijing 10048 |
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| Abstract: | Due to the existing of nonlinear friction, it is difficult to model in the traditional way. The friction and its describing method are firstly discussed. Then based on modeling the controlled object using neural network, the friction is compensated using adaptive inverse model ANN controller in parallel with a PID feedback controller. A simulation of a DC servo system is carried on and proved to be feasible. |
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| Keywords: | servo system neural network friction compensation adaptive inverse model |
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