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Optimal critic learning for robot control in time-varying environments

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posted on 2023-06-09, 09:24 authored by Chen Wang, Yanan LiYanan Li, Shuzhi Sam Ge, Tong Heng Lee
In this paper, optimal critic learning is developed for robot control in a time-varying environment. The unknown environment is described as a linear system with time-varying parameters, and impedance control is employed for the interaction control. Desired impedance parameters are obtained in the sense of an optimal realization of the composite of trajectory tracking and force regulation. Q-function based critic learning is developed to determine the optimal impedance parameters without the knowledge of the system dynamics. Simulation results are presented and compared with existing methods, and the efficacy of the proposed method is verified.

History

Publication status

  • Published

File Version

  • Accepted version

Journal

IEEE Transactions on Neural Networks and Learning Systems

ISSN

2162-237X

Publisher

Institute of Electrical and Electronics Engineers

Issue

10

Volume

26

Page range

2301-2310

Department affiliated with

  • Engineering and Design Publications

Notes

(c) 2015 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

2017-12-14

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