Metric learning to accelerate convergence of operator splitting methods for differentiable parametric programming
E King, J Kotary, F Fioretto, J Drgona - arXiv preprint arXiv:2404.00882, 2024 - arxiv.org
Recent work has shown a variety of ways in which machine learning can be used to
accelerate the solution of constrained optimization problems. Increasing demand for real …
accelerate the solution of constrained optimization problems. Increasing demand for real …
Driving from Vision through Differentiable Optimal Control
This paper proposes DriViDOC: a framework for Driving from Vision through Differentiable
Optimal Control, and its application to learn autonomous driving controllers from human …
Optimal Control, and its application to learn autonomous driving controllers from human …
Differentiable Predictive Control for Large-Scale Urban Road Networks
Transportation is a major contributor to CO2 emissions, making it essential to optimize traffic
networks to reduce energy-related emissions. This paper presents a novel approach to …
networks to reduce energy-related emissions. This paper presents a novel approach to …
Neural Differential Algebraic Equations
Differential-Algebraic Equations (DAEs) describe the temporal evolution of systems that
obey both differential and algebraic constraints. Of particular interest are systems that …
obey both differential and algebraic constraints. Of particular interest are systems that …
Differential Predictive Control of Residential Building HVACs for Maximizing Renewable Local Consumption and Supporting Fast Voltage Control
P Salter, C Wilkerson, Q Huang… - arXiv preprint arXiv …, 2024 - arxiv.org
High penetration of distributed energy resources in distribution systems, such as rooftop
solar PVs, has caused voltage fluctuations which are much faster than typical voltage control …
solar PVs, has caused voltage fluctuations which are much faster than typical voltage control …
Robust Differentiable Predictive Control with Safety Guarantees: A Predictive Safety Filter Approach
In this paper, we propose a novel predictive safety filter that is robust to bounded
perturbations and is combined with a learning-based control called differentiable predictive …
perturbations and is combined with a learning-based control called differentiable predictive …
Identification of Power Systems with Droop-Controlled Units Using Neural Ordinary Differential Equations
HMH Wolf, CA Hans - arXiv preprint arXiv:2411.08678, 2024 - arxiv.org
In future power systems, the detailed structure and dynamics may not always be fully known.
This is due to an increasing number of distributed energy resources, such as photovoltaic …
This is due to an increasing number of distributed energy resources, such as photovoltaic …
Real-Time Implementation of Differentiable Predictive Control on Embedded Microcontroller Hardware: A Case Study
J Boldocký, M Gulan, D Vrabie, J Drgoňa - IFAC-PapersOnLine, 2024 - Elsevier
This paper presents the embedded implementation of differentiable predictive control (DPC)
in a real-time control application with fast dynamics. DPC is a model-based policy …
in a real-time control application with fast dynamics. DPC is a model-based policy …
Scientific Machine Learning for Power System Dynamic Simulation
MA Bossart - 2024 - search.proquest.com
It is imperative to decarbonize the power system as quickly as possible to respond to the
threat of climate change. In pursuit of this goal, power systems around the world are …
threat of climate change. In pursuit of this goal, power systems around the world are …
[PDF][PDF] Centralised Decision Support in Maritime Vessel Traffic Services: A Polymatrix Game Solution
This article presents a concept for a centralised decision support system for local maritime
traffic. Given the increasing complexity of maritime traffic, particularly with the growing …
traffic. Given the increasing complexity of maritime traffic, particularly with the growing …