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Neural networks impedance control of robots interacting with environments
journal contribution
posted on 2023-06-09, 09:25 authored by Yanan LiYanan Li, Qun Zhang, Tong Heng Lee, Shuzhi Sam GeIn this paper, neural networks impedance control is proposed for robot-environment interaction. Iterative learning control is developed to make the robot dynamics follow a given target impedance model. To cope with the problem of unknown robot dynamics, neural networks are employed such that neither the robot structure nor the physical parameters are required for the control design. The stability and performance of the resulted closed-loop system are discussed through rigorous analysis and extensive remarks. The validity and feasibility of the proposed method are verified through simulation studies.
History
Publication status
- Published
File Version
- Accepted version
Journal
IET Control Theory and ApplicationsISSN
1751-8644Publisher
Institute of engineering and TechnologyExternal DOI
Issue
11Volume
7Page range
1509-1519Department affiliated with
- Engineering and Design Publications
Full text available
- Yes
Peer reviewed?
- Yes
Legacy Posted Date
2017-12-15First Open Access (FOA) Date
2017-12-15First Compliant Deposit (FCD) Date
2017-12-15Usage metrics
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