Zobrazeno 1 - 10
of 236
pro vyhledávání: '"Moritz Schulze"'
Publikováno v:
Automatisierungstechnik 71, no. 9 (2023): 736-747
Cooperative control is crucial for the effective operation of dynamical multi-agent systems. Especially for distributed control schemes, it is essential to exchange data between the agents. This becomes a privacy threat if the data is sensitive. Encr
Externí odkaz:
http://arxiv.org/abs/2412.13953
Autor:
von der Heyden, Jonas, Schlüter, Nils, Binfet, Philipp, Asman, Martin, Zdrallek, Markus, Jager, Tibor, Darup, Moritz Schulze
Smart grids feature a bidirectional flow of electricity and data, enhancing flexibility, efficiency, and reliability in increasingly volatile energy grids. However, data from smart meters can reveal sensitive private information. Consequently, the ad
Externí odkaz:
http://arxiv.org/abs/2411.14557
Neural networks (NN) have been successfully applied to approximate various types of complex control laws, resulting in low-complexity NN-based controllers that are fast to evaluate. However, when approximating control laws using NN, performance and s
Externí odkaz:
http://arxiv.org/abs/2411.03834
Encrypted computation opens up promising avenues across a plethora of application domains, including machine learning, health-care, finance, and control. Arithmetic homomorphic encryption, in particular, is a natural fit for cloud-based computational
Externí odkaz:
http://arxiv.org/abs/2410.20575
Recently, it has been observed that finite impulse response controllers are an excellent basis for encrypted control, where privacy-preserving controller evaluations via special cryptosystems are the main focus. Beneficial properties of FIR filters a
Externí odkaz:
http://arxiv.org/abs/2408.11959
Autor:
Adamek, Janis, Darup, Moritz Schulze
Federated learning (FL) schemes allow multiple participants to collaboratively train neural networks without the need to directly share the underlying data.However, in early schemes, all participants eventually obtain the same model. Moreover, the ag
Externí odkaz:
http://arxiv.org/abs/2407.13881
Publikováno v:
Proceedings of Machine Learning Research 242 (2024) 337-348
Piecewise regression is a versatile approach used in various disciplines to approximate complex functions from limited, potentially noisy data points. In control, piecewise regression is, e.g., used to approximate the optimal control law of model pre
Externí odkaz:
http://arxiv.org/abs/2407.06665
Aquifer thermal energy storages (ATES) are used to temporally store thermal energy in groundwater saturated aquifers. Typically, two storages are combined, one for heat and one for cold, to support heating and cooling of buildings. This way, the use
Externí odkaz:
http://arxiv.org/abs/2404.09786
The growing interconnectivity in control systems due to robust wireless communication and cloud usage paves the way for exciting new opportunities such as data-driven control and service-based decision-making. At the same time, connected systems are
Externí odkaz:
http://arxiv.org/abs/2404.04727
Although classical model predictive control with finite control sets (FCS-MPC) is quite a popular control method, particularly in the realm of power electronics systems, its direct data-driven predictive control (FCS-DPC) counterpart has received rel
Externí odkaz:
http://arxiv.org/abs/2404.02727