Published December 14, 2020
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Adaptive Control for Linearizable Systems Using On-Policy Reinforcement Learning
Abstract
The following topics are dealt with: control system synthesis; nonlinear control systems; linear systems; stability; optimisation; feedback; closed loop systems; Lyapunov methods; multi-agent systems; optimal control.
Additional Information
© 2020 IEEE. This work is funded by HICON-LEARN (design of HIgh CONfidence LEARNing-enabled systems), Defense Advanced Research Projects Agency award number FA8750-18-C-0101, and Provable High Confidence Human Robot Interactions, Office of Naval Research award number N00014-19-1-2066.Attached Files
Submitted - 2004.02766.pdf
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Additional details
- Alternative title
- Technical Report: Adaptive Control for Linearizable Systems Using On-Policy Reinforcement Learning
- Eprint ID
- 110732
- Resolver ID
- CaltechAUTHORS:20210903-222215502
- FA8750-18-C-0101
- Defense Advanced Research Projects Agency (DARPA)
- N00014-19-1-2066
- Office of Naval Research (ONR)
- Created
-
2021-09-07Created from EPrint's datestamp field
- Updated
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2021-09-07Created from EPrint's last_modified field