| Neural Network-Based Control of Networked Trilateral Teleoperation With Geometrically Unknown Constraints | |
Li ZJ(李智军); Xia YQ(夏元清); Wang, Dehong; Zhai, Di-Hua; Su CY(苏春翌); Zhao XG(赵新刚)
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| Department | 机器人学研究室 |
| Source Publication | IEEE TRANSACTIONS ON CYBERNETICS
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| ISSN | 2168-2267 |
| 2016 | |
| Volume | 46Issue:5Pages:1051-1064 |
| Indexed By | SCI ; EI |
| EI Accession number | 20151900836848 |
| WOS ID | WOS:000374989300002 |
| Contribution Rank | 1 |
| Funding Organization | National Natural Science Foundation of China [61174045, 61225015] ; Program for New Century Excellent Talents in University [NCET-12-0195] ; Ph.D. Programs Foundation of Ministry of Education of China [20130172110026] ; Foundation of State Key Laboratory of Robotics [2014-o07] ; Guangzhou Research Collaborative Innovation Projects [2014Y2-00507] ; National High-Tech Research and Development Program of China (863 Program) [2015AA042303] |
| Keyword | Hybrid Force-motion Control Kinematic Uncertainty Networked Trilateral Teleoperation Neural Networks |
| Abstract | Most studies on bilateral teleoperation assume known system kinematics and only consider dynamical uncertainties. However, many practical applications involve tasks with both kinematics and dynamics uncertainties. In this paper, trilateral teleoperation systems with dual-master-single-slave framework are investigated, where a single robotic manipulator constrained by an unknown geometrical environment is controlled by dual masters. The network delay in the teleoperation system is modeled as Markov chain-based stochastic delay, then asymmetric stochastic time-varying delays, kinematics and dynamics uncertainties are all considered in the force-motion control design. First, a unified dynamical model is introduced by incorporating unknown environmental constraints. Then, by exact identification of constraint Jacobian matrix, adaptive neural network approximation method is employed, and the motion/force synchronization with time delays are achieved without persistency of excitation condition. The neural networks and parameter adaptive mechanism are combined to deal with the system uncertainties and unknown kinematics. It is shown that the system is stable with the strict linear matrix inequality-based controllers. Finally, the extensive simulation experiment studies are provided to demonstrate the performance of the proposed approach. |
| Language | 英语 |
| WOS Headings | Science & Technology ; Technology |
| WOS Subject | Computer Science, Artificial Intelligence ; Computer Science, Cybernetics |
| WOS Keyword | OUTPUT-FEEDBACK CONTROL ; NONLINEAR-SYSTEMS ; BILATERAL TELEOPERATION ; COMMUNICATION DELAYS ; PREDICTIVE CONTROL ; STATE-FEEDBACK ; TIME-DELAYS ; OBSERVER ; DESIGN ; SYNCHRONIZATION |
| WOS Research Area | Computer Science |
| Citation statistics | |
| Document Type | 期刊论文 |
| Identifier | http://ir.sia.cn/handle/173321/18659 |
| Collection | 机器人学研究室 |
| Corresponding Author | Li ZJ(李智军) |
| Affiliation | 1.Key Laboratory of Autonomous System and Network Control, Ministry of Education, South China University of Technology, Guangzhou, China 2.College of Automation Science and Engineering, South China University of Technology, Guangzhou, China 3.State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, China 4.School of Automation, Beijing Institute of Technology, Beijing, China 5.Department of Mechanical and Industrial Engineering, Concordia University, Montreal, QC, Canada |
| Recommended Citation GB/T 7714 | Li ZJ,Xia YQ,Wang, Dehong,et al. Neural Network-Based Control of Networked Trilateral Teleoperation With Geometrically Unknown Constraints[J]. IEEE TRANSACTIONS ON CYBERNETICS,2016,46(5):1051-1064. |
| APA | Li ZJ,Xia YQ,Wang, Dehong,Zhai, Di-Hua,Su CY,&Zhao XG.(2016).Neural Network-Based Control of Networked Trilateral Teleoperation With Geometrically Unknown Constraints.IEEE TRANSACTIONS ON CYBERNETICS,46(5),1051-1064. |
| MLA | Li ZJ,et al."Neural Network-Based Control of Networked Trilateral Teleoperation With Geometrically Unknown Constraints".IEEE TRANSACTIONS ON CYBERNETICS 46.5(2016):1051-1064. |
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