14 citations · 49 across the 17 of their papers we have counts for
8 papers · 1 filter
Data Center Chiller Plant Optimization via Mixed-Integer Nonlinear Differentiable Predictive Control
Ján Boldocký, Cary Faulkner, Elad Michael +3
We present a computationally tractable framework for real-time predictive control of multi-chiller plants that involve both discrete and continuous control decisions coupled throug…
Differentiable Predictive Control with Safety Guarantees: A Control Barrier Function Approach
Wenceslao Shaw Cortez, Jan Drgona, Aaron Tuor +2
We develop a novel form of differentiable predictive control (DPC) with safety and robustness guarantees based on control barrier functions. DPC is an unsupervised learning-based m…
Neural Lyapunov Differentiable Predictive Control
Sayak Mukherjee, Ján Drgoňa, Aaron Tuor +2
We present a learning-based predictive control methodology using the differentiable programming framework with probabilistic Lyapunov-based stability guarantees. The neural Lyapuno…
Neuro-physical dynamic load modeling using differentiable parametric optimization
Shrirang Abhyankar, Jan Drgona, Andrew August +2
In this work, we investigate a data-driven approach for obtaining a reduced equivalent load model of distribution systems for electromechanical transient stability analysis. The pr…
Koopman-based Differentiable Predictive Control for the Dynamics-Aware Economic Dispatch Problem
Ethan King, Jan Drgona, Aaron Tuor +4
The dynamics-aware economic dispatch (DED) problem embeds low-level generator dynamics and operational constraints to enable near real-time scheduling of generation units in a powe…
Deep Learning Explicit Differentiable Predictive Control Laws for Buildings
Jan Drgona, Aaron Tuor, Soumya Vasisht +2
We present a differentiable predictive control (DPC) methodology for learning constrained control laws for unknown nonlinear systems. DPC poses an approximate solution to multipara…
Deep Learning Alternative to Explicit Model Predictive Control for Unknown Nonlinear Systems
Jan Drgona, Karol Kis, Aaron Tuor +2
We present differentiable predictive control (DPC) as a deep learning-based alternative to the explicit model predictive control (MPC) for unknown nonlinear systems. In the DPC fra…
Learning Constrained Adaptive Differentiable Predictive Control Policies With Guarantees
Jan Drgona, Aaron Tuor, Draguna Vrabie
We present differentiable predictive control (DPC), a method for learning constrained neural control policies for linear systems with probabilistic performance guarantees. We emplo…