[1]陈启宏,费树岷,宋爱国.遥操作机器人系统的预测控制[J].东南大学学报(自然科学版),2003,33(2):177-181.[doi:10.3969/j.issn.1001-0505.2003.02.015]
 Chen Qihong,Fei Shumin,Song Aiguo.Predictive control of teleoperation robot systems[J].Journal of Southeast University (Natural Science Edition),2003,33(2):177-181.[doi:10.3969/j.issn.1001-0505.2003.02.015]
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遥操作机器人系统的预测控制()
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《东南大学学报(自然科学版)》[ISSN:1001-0505/CN:32-1178/N]

卷:
33
期数:
2003年第2期
页码:
177-181
栏目:
自动化
出版日期:
2003-03-20

文章信息/Info

Title:
Predictive control of teleoperation robot systems
作者:
陈启宏1 费树岷1宋爱国2
1 东南大学自动化研究所, 南京 210096; 2 东南大学仪器科学与工程系, 南京 210096
Author(s):
Chen Qihong1 Fei Shumin1 Song Aiguo2
1 Research Institute of Automation, Southeast University, Nanjing 210096, China
2 Department of Instrument Science and Technology, Southeast University, Nanjing 210096, China
关键词:
遥操作 时延 神经网络 预测控制 观测器
Keywords:
teleoperation time delay neural network predictive control observer
分类号:
TP242
DOI:
10.3969/j.issn.1001-0505.2003.02.015
摘要:
遥操作机器人系统传输通道中存在通讯时延,造成系统不稳定和操作性能降低等问题.为了消除或减少时延的影响,利用前向神经网络建立环境模型,通过神经网络模型预测从机械手受力,并用时间前向观测器预测从机械手状态; 然后用力、位置和速度反馈对系统进行设计,使得系统在环境模型未知的条件下稳定,还能获得良好的透明性; 最后,将预测方法与无源控制方法进行切换,保证系统在环境剧变时的稳定性.实验结果表明了该方法的有效性.
Abstract:
The communication time delay in communication channels of a teleoperation robot system conduces to instability and bad performance of the system. In order to eliminate or reduce the effect of time delays, back propogation neural network is used to build the model of environment. Force and states of the slave are predicted through the neural network model and time forward observer. Moreover, force,position and velocity feedback are proposed, control parameters are designed and controllers are switched between predictive control and passive control to ensure the stability and performance of the system. The experimental results prove the effectiveness of this method.

参考文献/References:

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备注/Memo

备注/Memo:
基金项目: 国家863高技术资助项目(863-2001AA423240).
作者简介: 陈启宏(1975—),男,博士生; 费树岷(联系人),男,博士,教授,博士生导师,smfei@seu.edu.cn.
更新日期/Last Update: 2003-03-20