Neuro-predictive control based self-tuning of PID controllers. - Corneliu Lazar; Sorin Carari; Draguna L. Vrabie; Marius Kloetzer (ESANN, 2004)

Model-free Approximate Dynamic Programming Schemes for Linear Systems. - Asma Al-Tamimi; Draguna L. Vrabie; Murad Abu-Khalaf; Frank L. Lewis (IJCNN, 2007)

Adaptive optimal control algorithm for continuous-time nonlinear systems based on policy iteration. - Draguna L. Vrabie; Frank L. Lewis (CDC, 2008)

Neural Network-Based Adaptive Optimal Controller - A Continuous-Time Formulation. - Draguna L. Vrabie; Frank L. Lewis; Daniel S. Levine 001 (ICIC (3), 2008)

Online policy iteration based algorithms to solve the continuous-time infinite horizon optimal control problem. - Kyriakos G. Vamvoudakis; Draguna L. Vrabie; Frank L. Lewis (ADPRL, 2009)

Generalized Policy Iteration for continuous-time systems. - Draguna L. Vrabie; Frank L. Lewis (IJCNN, 2009)

Adaptive optimal control for continuous-time linear systems based on policy iteration. - Draguna L. Vrabie; Octavian C. Pastravanu; Murad Abu-Khalaf; Frank L. Lewis (Autom., 2009)

Neural network approach to continuous-time direct adaptive optimal control for partially unknown nonlinear systems. - Draguna L. Vrabie; Frank L. Lewis (Neural Networks, 2009)

Integral Reinforcement Learning for online computation of feedback Nash strategies of nonzero-sum differential games. - Draguna L. Vrabie; Frank L. Lewis (CDC, 2010)

Adaptive Dynamic Programming algorithm for finding online the equilibrium solution of the two-player zero-sum differential game. - Draguna L. Vrabie; Frank L. Lewis (IJCNN, 2010)

Online adaptive learning of optimal control solutions using integral reinforcement learning. - Kyriakos G. Vamvoudakis; Draguna L. Vrabie; Frank L. Lewis (ADPRL, 2011)

Parameter estimation of a building system model and impact of estimation error on closed-loop performance. - Sorin C. Bengea; Veronica Adetola; Keunmo Kang; Michael J. Liba; Draguna L. Vrabie; Robert R. Bitmead; Satish Narayanan (CDC/ECC, 2011)

Towards a framework for selection of supervisory control for commercial buildings: HVAC system energy efficiency. - Thiagarajan Ramachandran; Soumya Kundu; Yan Chen; Draguna L. Vrabie (ACC, 2017)

A Learning Framework for Control-Oriented Modeling of Buildings. - Javier Rubio-Herrero; Vikas Chandan; Charles Siegel; Abhinav Vishnu; Draguna L. Vrabie (ICMLA, 2017)

Optimal Energy Consumption Forecast for Grid Responsive Buildings: A Sensitivity Analysis. - Soumya Kundu; Thiagarajan Ramachandran; Yan Chen; Draguna L. Vrabie (CCTA, 2018)

Prioritized Threshold Allocation for Distributed Frequency Response. - Sai Pushpak Nandanoori; Soumya Kundu; Draguna L. Vrabie; Karan Kalsi; Jianming Lian (CCTA, 2018)

Generative Adversarial Network based Autoencoder: Application to Fault Detection Problem for Closed Loop Dynamical Systems. - Indrasis Chakraborty; Rudrasis Chakraborty; Draguna L. Vrabie (DX@Safeprocess, 2018)

A sequential DNN based Baseline Energy Prediction Framework with Long term Error Mitigation. - Indrasis Chakraborty; Vikas Chandan; Draguna L. Vrabie (e-Energy, 2019)

Online Learning for Commercial Buildings. - Jin Dong; Thiagarajan Ramachandran; Piljae Im; Sen Huang; Vikas Chandan; Draguna L. Vrabie; P. Teja Kuruganti (e-Energy, 2019)

Coupling Power System Dynamics and Building Dynamics to Enabling Building-to-Grid Integration. - Yangyang Fu; Sen Huang; Draguna L. Vrabie; Wangda Zuo (Modelica, 2019)

Theoretical Development of Controller Transfer applied to Dynamical Systems. - Indrasis Chakraborty; Yan Chen; Jing Li; Draguna L. Vrabie (e-Energy, 2020)

All you need to know about model predictive control for buildings. - Ján Drgona; Javier Arroyo; Iago Cupeiro Figueroa; David H. Blum; Krzysztof Arendt; Donghun Kim; Enric Perarnau Ollé; Juraj Oravec; Michael Wetter; Draguna L. Vrabie; Lieve Helsen (Annu. Rev. Control., 2020)

Constrained Neural Ordinary Differential Equations with Stability Guarantees. - Aaron Tuor; Ján Drgona; Draguna L. Vrabie (CoRR, 2020)

Constrained Physics-Informed Deep Learning for Stable System Identification and Control of Unknown Linear Systems. - Ján Drgona; Aaron Tuor; Draguna L. Vrabie (CoRR, 2020)

Differentiable Predictive Control: An MPC Alternative for Unknown Nonlinear Systems using Constrained Deep Learning. - Ján Drgona; Karol Kis; Aaron Tuor; Draguna L. Vrabie; Martin Klauco (CoRR, 2020)

Physics-constrained Deep Learning of Multi-zone Building Thermal Dynamics. - Ján Drgona; Aaron Randall Tuor; Vikas Chandan; Draguna L. Vrabie (CoRR, 2020)

Spectral Analysis and Stability of Deep Neural Dynamics. - Ján Drgona; Elliott Skomski; Soumya Vasisht; Aaron Tuor; Draguna L. Vrabie (CoRR, 2020)

Learning and Information Manipulation: Repeated Hypergames for Cyber-Physical Security. - Craig Bakker; Arnab Bhattacharya 008; Samrat Chatterjee; Draguna L. Vrabie (IEEE Control. Syst. Lett., 2020)

Hypergames and Cyber-Physical Security for Control Systems. - Craig Bakker; Arnab Bhattacharya 008; Samrat Chatterjee; Draguna L. Vrabie (ACM Trans. Cyber Phys. Syst., 2020)

Occupancy-Driven Stochastic Decision Framework for Ranking Commercial Building Loads. - Milan Jain; Soumya Kundu; Arnab Bhattacharya 008; Sen Huang; Vikas Chandan; Nikitha Radhakrishnan; Veronica Adetola; Draguna L. Vrabie (ACC, 2021)

Constrained Block Nonlinear Neural Dynamical Models. - Elliott Skomski; Soumya Vasisht; Colby Wight; Aaron Tuor; Ján Drgona; Draguna L. Vrabie (ACC, 2021)

Co-Design of Commercial Building HVAC using Bayesian Optimization. - Soumya Vasisht; Arnab Bhattacharya 008; Sen Huang; Himanshu Sharma; Veronica Adetola; Draguna L. Vrabie (ACC, 2021)

Randomized Algorithms for Scientific Computing (RASC). - Aydin Buluç; Tamara G. Kolda; Stefan M. Wild; Mihai Anitescu; Anthony M. DeGennaro; John Jakeman; Chandrika Kamath 001; Ramakrishnan Kannan; Miles E. Lopes; Per-Gunnar Martinsson; Kary L. Myers; Jelani Nelson; et al. (CoRR, 2021)

Sparse Control Synthesis for Uncertain Responsive Loads with Stochastic Stability Guarantees. - Sai Pushpak Nandanoori; Soumya Kundu; Jianming Lian; Umesh Vaidya; Draguna L. Vrabie; Karanjit Kalsi (CoRR, 2021)

Deep Learning Explicit Differentiable Predictive Control Laws for Buildings. - Ján Drgona; Aaron Tuor; Soumya Vasisht; Elliott Skomski; Draguna L. Vrabie (CoRR, 2021)

Metagames and Hypergames for Deception-Robust Control. - Craig Bakker; Arnab Bhattacharya 008; Samrat Chatterjee; Draguna L. Vrabie (ACM Trans. Cyber Phys. Syst., 2021)

Koopman-based Differentiable Predictive Control for the Dynamics-Aware Economic Dispatch Problem. - Ethan King; Ján Drgona; Aaron Tuor; Shrirang Abhyankar; Craig Bakker; Arnab Bhattacharya 008; Draguna L. Vrabie (ACC, 2022)

Neural Lyapunov Differentiable Predictive Control. - Sayak Mukherjee; Ján Drgona; Aaron Tuor; Mahantesh Halappanavar; Draguna L. Vrabie (CDC, 2022)

Differentiable Predictive Control with Safety Guarantees: A Control Barrier Function Approach. - Wenceslao Shaw-Cortez; Ján Drgona; Aaron Tuor; Mahantesh Halappanavar; Draguna L. Vrabie (CDC, 2022)

Data-driven Stabilization of Discrete-time Control-affine Nonlinear Systems: A Koopman Operator Approach. - Subhrajit Sinha; Sai Pushpak Nandanoori; Ján Drgona; Draguna L. Vrabie (ECC, 2022)

Learning Distributed Geometric Koopman Operator for Sparse Networked Dynamical Systems. - Sayak Mukherjee; Sai Pushpak Nandanoori; Sheng Guan; Khushbu Agarwal; Subhrajit Sinha; Soumya Kundu; Seemita Pal; Yinghui Wu 001; Draguna L. Vrabie; Sutanay Choudhury (LoG, 2022)

Learning Stochastic Parametric Differentiable Predictive Control Policies. - Ján Drgona; Sayak Mukherjee; Aaron Tuor; Mahantesh Halappanavar; Draguna L. Vrabie (CoRR, 2022)

Structural Inference of Networked Dynamical Systems with Universal Differential Equations. - James Koch; Zhao Chen; Aaron Tuor; Ján Drgona; Draguna L. Vrabie (CoRR, 2022)

Domain-aware Control-oriented Neural Models for Autonomous Underwater Vehicles. - Wenceslao Shaw-Cortez; Soumya Vasisht; Aaron Tuor; Ján Drgona; Draguna L. Vrabie (CoRR, 2022)

Physics-Informed Machine Learning for Modeling and Control of Dynamical Systems. - Truong X. Nghiem; Ján Drgona; Colin N. Jones; Zoltán Nagy 002; Roland Schwan; Biswadip Dey; Ankush Chakrabarty; Stefano Di Cairano; Joel A. Paulson; Andrea Carron; Melanie N. Zeilinger; Wenceslao Shaw-Cortez; et al. (ACC, 2023)

Data-Driven Control: Theory and Applications. - Damoon Soudbakhsh; Anuradha M. Annaswamy; Yan Wang 075; Steven L. Brunton; Joseph E. Gaudio; Heather S. Hussain; Draguna L. Vrabie; Ján Drgona; Dimitar P. Filev (ACC, 2023)

EXARL-PARS: Parallel Augmented Random Search Using Reinforcement Learning at Scale for Applications in Power Systems. - Himanshu Sharma; Joshua D. Suetterlein; Sumathi Lakshmiranganatha; Thomas Flynn 001; Draguna L. Vrabie; Christine Sweeney; Vinay Ramakrishnaiah (e-Energy (Companion), 2023)

Robust Differentiable Predictive Control with Safety Guarantees: A Predictive Safety Filter Approach. - Wenceslao Shaw-Cortez; Ján Drgona; Draguna L. Vrabie; Mahantesh Halappanavar (CoRR, 2023)

Codesign for Extreme Heterogeneity: Integrating Custom Hardware With Commodity Computing Technology to Support Next-Generation HPC Converged Workloads. - James A. Ang; Kevin J. Barker; Draguna L. Vrabie; Gokcen Kestor (IEEE Internet Comput., 2023)

Deep Multi-Agent Reinforcement Learning for Real-World Signalized Traffic Corridor Control. - Salman Shuvo; Sayak Mukherjee; Samrat Chatterjee; Sonja Glavaski; Draguna L. Vrabie; Geline Canayon; Matthew Juckes; Raimundo Rodulfo (ICMLA, 2024)

Neural Differential Algebraic Equations. - James Koch; Madelyn Shapiro; Himanshu Sharma; Draguna L. Vrabie; Ján Drgona (CoRR, 2024)

Differentiable Predictive Control for Large-Scale Urban Road Networks. - Renukanandan Tumu; Wenceslao Shaw-Cortez; Ján Drgona; Draguna L. Vrabie; Sonja Glavaski (CoRR, 2024)

Differentiable Predictive Control for Robotics: A Data-Driven Predictive Safety Filter Approach. - John Viljoen; Wenceslao Shaw-Cortez; Ján Drgona; Sebastian East; Masayoshi Tomizuka; Draguna L. Vrabie (CoRR, 2024)

Learning Constrained Parametric Differentiable Predictive Control Policies With Guarantees. - Ján Drgona; Aaron Tuor; Draguna L. Vrabie (IEEE Trans. Syst. Man Cybern. Syst., 2024)

Safe Physics-informed Machine Learning for Dynamics and Control. - Ján Drgona; Truong X. Nghiem; Thomas Beckers 001; Mahyar Fazlyab; Enrique Mallada; Colin N. Jones; Draguna L. Vrabie; Steven L. Brunton; Rolf Findeisen (ACC, 2025)

Physics-informed machine learning for building performance simulation-A review of a nascent field. - Zixin Jiang; Xuezheng Wang; Han Li; Tianzhen Hong; Fengqi You; Ján Drgona; Draguna L. Vrabie; Bing Dong (CoRR, 2025)

A Method for Learning to Solve Parametric Bilevel Optimization with Coupling Constraints. - James Kotary; Himanshu Sharma; Ethan King; Draguna L. Vrabie; Ferdinando Fioretto; Ján Drgona (CoRR, 2025)