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Grüne, Lars ; Sperl, Mario ; Chatterjee, Debasish:
Representation of practical nonsmooth control Lyapunov functions by piecewise affine functions and neural networks.
In: Systems & Control Letters.
Bd. 202
(2025)
.
- 106103.
ISSN 1872-7956
DOI: https://doi.org/10.1016/j.sysconle.2025.106103
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| Projekttitel: |
Offizieller Projekttitel Projekt-ID Curse-of-dimensionality-free nonlinear optimal feedback control with deep neural networks. A compositionality-based approach via Hamilton-Jacobi-Bellman PDEs 463912816 |
|---|---|
| Projektfinanzierung: |
Deutsche Forschungsgemeinschaft |
Abstract
In this paper we give conditions under which control Lyapunov functions exist that can be represented by either piecewise affine functions or by neural networks with a suitable number of ReLU layers. The results provide a theoretical foundation for recent computational approaches for computing control Lyapunov functions with optimization-based and machine-learning techniques.
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Representation of practical nonsmooth control Lyapunov functions by piecewise affine functions and neural networks. (deposited 07 Jan 2025 14:17)
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Representation of practical nonsmooth control Lyapunov functions by piecewise affine functions and neural networks. (deposited 10 Feb 2025 07:40)
- Representation of practical nonsmooth control Lyapunov functions by piecewise affine functions and neural networks. (deposited 28 Apr 2025 07:24) [Aktuelle Anzeige]
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Representation of practical nonsmooth control Lyapunov functions by piecewise affine functions and neural networks. (deposited 10 Feb 2025 07:40)