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20152026
most citedError bounds for maxout neural network approximations of model predictive control

6 citations · 41 across the 34 of their papers we have counts for

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6 papers · 1 filter

eess.SY2025

MPC for Aquifer Thermal Energy Storage Systems Using ARX Models

Johannes van Randenborgh, Moritz Schulze Darup

An aquifer thermal energy storage (ATES) can mitigate CO2 emissions of heating, ventilation, and air conditioning (HVAC) systems for buildings. In application, an ATES keeps large…

eess.SY2025

A lightweight numerical model for predictive control of borehole thermal energy storages

Johannes van Randenborgh, Steffen Daniel, Moritz Schulze Darup

Borehole thermal energy storage (BTES) can reduce the operation of fossil fuel-based heating, ventilation, and air conditioning systems for buildings. With BTES, thermal energy is…

eess.SY2025★ 1 cited

On data usage and predictive behavior of data-driven predictive control with 1-norm regularization

Manuel Klädtke, Moritz Schulze Darup

We investigate the data usage and predictive behavior of data-driven predictive control (DPC) with 1-norm regularization. Our analysis enables the offline removal of unused data an…

eess.SY2025

A mixed-integer framework for analyzing neural network-based controllers for piecewise affine systems with bounded disturbances

Dieter Teichrib, Moritz Schulze Darup

We present a method for representing the closed-loop dynamics of piecewise affine (PWA) systems with bounded additive disturbances and neural network-based controllers as mixed-int…

eess.SY2025★ 1 cited

A moving horizon estimator for aquifer thermal energy storages

Johannes van Randenborgh, Moritz Schulze Darup

Aquifer thermal energy storages (ATES) represent groundwater saturated aquifers that store thermal energy in the form of heated or cooled groundwater. Combining two ATES, one can h…

eess.SY2025

Towards explainable data-driven predictive control with regularizations

Manuel Klädtke, Moritz Schulze Darup

Data-driven predictive control (DPC), using linear combinations of recorded trajectory data, has recently emerged as a popular alternative to traditional model predictive control (…