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Journal Articles Systems and Control Letters Year : 2016

Fast diffeomorphic matching to learn globally asymptotically stable nonlinear dynamical systems

Abstract

We propose a new diffeomorphic matching algorithm and use it to learn nonlinear dynamical systems with the guarantee that the learned systems have global asymptotic stability. For a given set of demonstration trajectories, we compute a diffeomorphism that maps forward orbits of a reference stable time-invariant system onto the demonstrations, thereby deforming the whole reference system into one that reproduces the demonstrations, and is still stable.
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Dates and versions

hal-01394886 , version 1 (10-11-2016)

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Nicolas Perrin, Philipp Schlehuber-Caissier. Fast diffeomorphic matching to learn globally asymptotically stable nonlinear dynamical systems. Systems and Control Letters, 2016, 96, pp.51 - 59. ⟨10.1016/j.sysconle.2016.06.018⟩. ⟨hal-01394886⟩
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