Adaptive neural network tracking control for manipulators with uncertainties
Long Cheng; Zeng-Guang Hou; Min Tan; H. Wang
2008
会议名称the 17th World Congress The International Federation of Automatic Contro
会议日期July 6-11, 2008
会议地点Seoul
会议举办国South Korea
摘要An adaptive neural network controller is proposed to deal with the end-effector tracking problem of manipulators with uncertainties. By employing the adaptive Jacobian scheme, neural networks, and backstepping technique, the torque controller can be obtained which is demonstrated to be stable by the Lyapunov approach. The updating laws for designed controller parameters are derived by the projection method, and the tracking error can be reduced as small as possible. The favorable features of the proposed controller lie in that: (1) the uncertainty in manipulator kinematics is taken into account; (2) the “linearity-in-parameters” assumption for the uncertain terms in dynamics of manipulators is no longer necessary; (3) effects of external disturbances are considered in the controller design. Finally, the satisfactory performance of the proposed approach is illustrated by simulation results on a PUMA 560 robot.
文献类型会议论文
条目标识符http://ir.ia.ac.cn/handle/173211/23160
专题复杂系统管理与控制国家重点实验室_先进机器人
推荐引用方式
GB/T 7714
Long Cheng,Zeng-Guang Hou,Min Tan,et al. Adaptive neural network tracking control for manipulators with uncertainties[C],2008.
条目包含的文件
条目无相关文件。
个性服务
推荐该条目
保存到收藏夹
查看访问统计
导出为Endnote文件
谷歌学术
谷歌学术中相似的文章
[Long Cheng]的文章
[Zeng-Guang Hou]的文章
[Min Tan]的文章
百度学术
百度学术中相似的文章
[Long Cheng]的文章
[Zeng-Guang Hou]的文章
[Min Tan]的文章
必应学术
必应学术中相似的文章
[Long Cheng]的文章
[Zeng-Guang Hou]的文章
[Min Tan]的文章
相关权益政策
暂无数据
收藏/分享
所有评论 (0)
暂无评论
 

除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。