Force Sensorless Admittance Control With Neural Learning for Robots With Actuator Saturation
文献类型：期刊论文
| 作者 | Peng, Guangzhu3; Yang, Chenguang6; He, Wei4; Chen, C. L. Philip1,2,5 |
| 刊名 | IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
 |
| 出版日期 | 2020-04-01 |
| 卷号 | 67期号:4页码:3138-3148 |
| ISSN号 | 0278-0046 |
| 关键词 | Robot sensing systems Admittance Manipulators Force Torque Adaptation models Adaptive neural control admittance control neural networks (NNs) observer |
| DOI | 10.1109/TIE.2019.2912781 |
| 通讯作者 | Yang, Chenguang(cyang@ieee.org) |
| 英文摘要 | In this paper, we present a sensorless admittance control scheme for robotic manipulators to interact with unknown environments in the presence of actuator saturation. The external environment is defined as linear models with unknown dynamics. Using admittance control, the robotic manipulator is controlled to be compliant with external torque from the environment. The external torque acted on the end-effector is estimated by using a disturbance observer based on generalized momentum. The model uncertainties are solved by using radial basis neural networks (NNs). To guarantee the tracking performance and tackle the effect of actuator saturation, an adaptive NN controller integrating an auxiliary system is designed to handle the actuator saturation. By employing Lyapunov stability theory, the stability of the closed-loop system is achieved. The experiments on the Baxter robot are implemented to verify the effectiveness of the proposed method. |
| WOS关键词 | NONLINEAR-SYSTEMS ; IMPEDANCE CONTROL ; DESIGN |
| 资助项目 | Engineering and Physical Sciences Research Council[EP/S001913] ; National Natural Science Foundation of China[61751202] ; National Natural Science Foundation of China[61572540] ; Key Program for International S&T Cooperation Projects of China[2016YFE0121200] ; Macau Science and Technology Development Fund[019/2015/A1] ; Macau Science and Technology Development Fund[079/2017/A2] ; Macau Science and Technology Development Fund[024/2015/AMJ] ; University of Macau |
| WOS研究方向 | Automation & Control Systems ; Engineering ; Instruments & Instrumentation |
| 语种 | 英语 |
| 出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
| WOS记录号 | WOS:000507307000061 |
| 资助机构 | Engineering and Physical Sciences Research Council ; National Natural Science Foundation of China ; Key Program for International S&T Cooperation Projects of China ; Macau Science and Technology Development Fund ; University of Macau |
| 源URL | [http://ir.ia.ac.cn/handle/173211/29539]  |
| 专题 | 离退休人员 |
| 通讯作者 | Yang, Chenguang |
| 作者单位 | 1.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100080, Peoples R China 2.Dalian Maritime Univ, Dept Nav, Dalian 116026, Peoples R China 3.Univ Macau, Dept Comp & Informat Sci, Fac Sci & Technol, Macau 999078, Peoples R China 4.Univ Sci & Technol Beijing, Sch Automat & Elect Engn, Beijing 100083, Peoples R China 5.Univ Macau, Fac Sci & Technol, Macau 999078, Peoples R China 6.Univ West England, Bristol Robot Lab, Bristol BS16 1QY, Avon, England |
| 推荐引用方式 GB/T 7714 | Peng, Guangzhu,Yang, Chenguang,He, Wei,et al. Force Sensorless Admittance Control With Neural Learning for Robots With Actuator Saturation[J]. IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS,2020,67(4):3138-3148. |
| APA | Peng, Guangzhu,Yang, Chenguang,He, Wei,&Chen, C. L. Philip.(2020).Force Sensorless Admittance Control With Neural Learning for Robots With Actuator Saturation.IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS,67(4),3138-3148. |
| MLA | Peng, Guangzhu,et al."Force Sensorless Admittance Control With Neural Learning for Robots With Actuator Saturation".IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS 67.4(2020):3138-3148. |
入库方式： OAI收割
来源：自动化研究所
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