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Impedance learning for robots interacting with unknown environments

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journal contribution
posted on 2023-06-09, 09:25 authored by Yanan LiYanan Li, Shuzhi Sam Ge
In this paper, impedance learning is investigated for robots interacting with unknown environments. A twoloop control framework is employed and adaptive control is developed for the inner-loop position control. The environments are described as time-varying systems with unknown parameters in the state-space form. The gradient-following scheme and betterment scheme are employed to obtain a desired impedance model, subject to unknown environments. The desired interaction performance is achieved in the sense that a defined cost function is minimized. Simulation and experiment studies are carried out to verify the validity of the proposed method.

History

Publication status

  • Published

File Version

  • Accepted version

Journal

IEEE Transactions on Control Systems Technology

ISSN

1063-6536

Publisher

Institute of Electrical and Electronics Engineers

Issue

4

Volume

22

Page range

1422-1432

Department affiliated with

  • Engineering and Design Publications

Notes

(c) 2013 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

Full text available

  • Yes

Peer reviewed?

  • Yes

Legacy Posted Date

2017-12-15

First Open Access (FOA) Date

2017-12-15

First Compliant Deposit (FCD) Date

2017-12-15

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