70 citations · 150 across the 31 of their papers we have counts for
6 papers · 1 filter
Physics-constrained Deep Learning of Multi-zone Building Thermal Dynamics
Jan Drgona, Aaron R. Tuor, Vikas Chandan +1
We present a physics-constrained control-oriented deep learning method for modeling building thermal dynamics. The proposed method is based on the systematic encoding of physics-ba…
Dissipative Deep Neural Dynamical Systems
Jan Drgona, Soumya Vasisht, Aaron Tuor +1
In this paper, we provide sufficient conditions for dissipativity and local asymptotic stability of discrete-time dynamical systems parametrized by deep neural networks. We leverag…
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…
Constrained Neural Ordinary Differential Equations with Stability Guarantees
Aaron Tuor, Jan Drgona, Draguna Vrabie
Differential equations are frequently used in engineering domains, such as modeling and control of industrial systems, where safety and performance guarantees are of paramount impo…
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…
Model Predictive Control of Discrete-Continuous Energy Systems via Generalized Disjunctive Programming
Arnab Bhattacharya, Xu Ma, Draguna Vrabie
Generalized Disjunctive Programming (GDP) provides an alternative framework to model optimization problems with both discrete and continuous variables. The key idea behind GDP invo…