Projekte: Curse-of-dimensionality-free nonlinear optimal feedback control with deep neural networks. A compositionality-based approach via Hamilton-Jacobi-Bellman PDEs

Sperl, Mario ; Saluzzi, Luca ; Kalise, Dante ; Grüne, Lars:
Separable approximations of optimal value functions and their representation by neural networks.
Bayreuth , 2025 . - 20 S.
DOI: https://doi.org/10.48550/arXiv.2502.08559

Sperl, Mario ; Mysliwitz, Jonas ; Grüne, Lars:
On the Existence and Neural Network Representation of Separable Control Lyapunov Functions.
Bayreuth , 2025 . - 11 S.
DOI: https://doi.org/10.15495/EPub_UBT_00008463

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.
DOI: https://doi.org/10.1016/j.sysconle.2025.106103

Sperl, Mario ; Saluzzi, Luca ; Grüne, Lars ; Kalise, Dante:
Separable approximations of optimal value functions under a decaying sensitivity assumption.
In: 62nd IEEE Conference on Decision and Control (CDC) 2023. - Singapore, Singapore , 2023 . - S. 259-264
DOI: https://doi.org/10.1109/CDC49753.2023.10383497

Grüne, Lars ; Sperl, Mario:
Examples for separable control Lyapunov functions and their neural network approximation.
In: IFAC-PapersOnLine. Bd. 56 (2023) Heft 1 . - S. 19-24.
DOI: https://doi.org/10.1016/j.ifacol.2023.02.004