Title data
Grüne, Lars ; Sperl, Mario:
Examples for existence and non-existence of separable control Lyapunov functions.
Bayreuth
,
2022
. - 6 p.
DOI: https://doi.org/10.15495/EPub_UBT_00006664
Project information
Project title: |
Project's official title Project's id Curse-of-dimensionality-free nonlinear optimal feedback control with deep neural networks. A compositionality-based approach via Hamilton-Jacobi-Bellman PDEs GR 1569/23-1 |
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Project financing: |
Deutsche Forschungsgemeinschaft |
Abstract in another language
In this paper, we consider nonlinear control systems and discuss the existence of a separable control Lyapunov function. To this end, we assume that the system can be decomposed into subsystems and formulate conditions such that a weighted sum of Lyapunov functions of the subsystems yields a control Lyapunov function of the overall system. Since deep neural networks are capable of approximating separable functions without suffering from the curse of dimensionality, we can thus identify systems where an efficient approximating of a control Lyapunov function via a deep neural network is possible. A corresponding network architecture and training algorithm are proposed. Further, numerical examples illustrate the behavior of the algorithm.
Further data
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- Examples for existence and non-existence of separable control Lyapunov functions. (deposited 01 Oct 2022 21:00) [Currently Displayed]