Learning stabilizable nonlinear dynamics with contraction-based regularization
© The Author(s) 2020. We propose a novel framework for learning stabilizable nonlinear dynamical systems for continuous control tasks in robotics. The key contribution is a control-theoretic regularizer for dynamics fitting rooted in the notion of stabilizability, a constraint which guarantees the e...
Main Authors: | , , , , |
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Format: | Article |
Language: | English |
Published: |
SAGE Publications,
2022-01-24T19:13:39Z.
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Subjects: | |
Online Access: | Get fulltext |