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Optimal critic learning for robot control in time-varying environments
journal contribution
posted on 2023-06-09, 09:24 authored by Chen Wang, Yanan LiYanan Li, Shuzhi Sam Ge, Tong Heng LeeIn 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 SystemsISSN
2162-237XPublisher
Institute of Electrical and Electronics EngineersExternal DOI
Issue
10Volume
26Page range
2301-2310Department 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
2017-12-15First Open Access (FOA) Date
2017-12-15First Compliant Deposit (FCD) Date
2017-12-14Usage metrics
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