中国科学院机构知识库网格系统: 检索

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	Disturbance Rejection Control for Underwater Free-Floating Manipulation 期刊论文 OAI收割 IEEE-ASME TRANSACTIONS ON MECHATRONICS, 2021, 页码: 9 作者: Lv, Jiaqi; Wang, Yu; Tang, Chong; Wang, Shuo; Xu, Wenxing \| 收藏 \| 浏览/下载：42/0 \| 提交时间：2022/01/27 Manipulators Task analysis Propulsion Estimation Disturbance observers Mechatronics IEEE transactions Disturbance observer-based control (DOBC) fast arctangent nonsingularity terminal sliding mode controller (FANTSMC) underwater biomimetic vehicle-manipulator system (UBVMS) underwater manipulation
	Active Disturbance Rejection Control for a Fluid-Driven Hand Rehabilitation Device 期刊论文 OAI收割 IEEE-ASME TRANSACTIONS ON MECHATRONICS, 2021, 卷号: 26, 期号: 2, 页码: 841-853 作者: Li, Houcheng; Cheng, Long; Li, Zhengwei; Xue, Wenchao \| 收藏 \| 浏览/下载：29/0 \| 提交时间：2021/06/07 Actuators Exoskeletons Performance evaluation Training IEEE transactions Mechatronics Active disturbance rejection control extended state observer extension motion hand rehabilitation parameter selection transient steady-state performance
	Active Disturbance Rejection Control for a Fluid-Driven Hand Rehabilitation Device 期刊论文 OAI收割 IEEE-ASME TRANSACTIONS ON MECHATRONICS, 2021, 卷号: 26, 期号: 2, 页码: 841-853 作者: Li, Houcheng; Cheng, Long; Li, Zhengwei; Xue, Wenchao \| 收藏 \| 浏览/下载：27/0 \| 提交时间：2021/10/26 Actuators Exoskeletons Performance evaluation Training IEEE transactions Mechatronics Active disturbance rejection control extended state observer extension motion hand rehabilitation parameter selection transient steady-state performance
	Joining Force of Human Muscular Task Planning With Robot Robust and Delicate Manipulation for Programming by Demonstration 期刊论文 OAI收割 IEEE-ASME TRANSACTIONS ON MECHATRONICS, 2020, 卷号: 25 作者: Wang, Fei; Zhou, Xingqun; Wang, Jianhui; Zhang, Xing; He, Zhenquan \| 收藏 \| 浏览/下载：36/0 \| 提交时间：2020/11/30 Task analysis Robot sensing systems Gesture recognition IEEE transactions Mechatronics Robotic assembly Implicit muscular task planning multisource information fusion programming by demonstration reinforcement learning