Please use this identifier to cite or link to this item: https://doi.org/10.1049/iet-cta.2012.1032
Title: Neural networks impedance control of robots interacting with environments
Authors: Li, Y.
Ge, S.S. 
Zhang, Q. 
Lee, T.H. 
Issue Date: 2013
Source: Li, Y., Ge, S.S., Zhang, Q., Lee, T.H. (2013). Neural networks impedance control of robots interacting with environments. IET Control Theory and Applications 7 (11) : 1509-1519. ScholarBank@NUS Repository. https://doi.org/10.1049/iet-cta.2012.1032
Abstract: In this study, neural networks (NN) 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, NN 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. © The Institution of Engineering and Technology 2013.
Source Title: IET Control Theory and Applications
URI: http://scholarbank.nus.edu.sg/handle/10635/56786
ISSN: 17518644
DOI: 10.1049/iet-cta.2012.1032
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