Jan Drgona

Hivatkozott rá

	Összes	2020 óta
Hivatkozások	2518	2354
h-index	23	20
i10-index	34	33

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Draguna VrabiePacific Northwest National LaboratoryE-mail megerősítve itt: pnnl.gov
Aaron TuorWestern Washington UniversityE-mail megerősítve itt: pnnl.gov
Helsen LieveProfessor of Mechanical Engineering, KU LeuvenE-mail megerősítve itt: mech.kuleuven.be
Michal KvasnicaFull Professor at Slovak University of Technology in BratislavaE-mail megerősítve itt: stuba.sk
Martin KlaucoHead of department | Senior ResearcherE-mail megerősítve itt: stuba.sk
Mahantesh HalappanavarChief Data Scientist & Group Leader, Pacific Northwest National LaboratoryE-mail megerősítve itt: pnnl.gov
Michael WetterLBNL, Berkeley, CAE-mail megerősítve itt: lbl.gov
Wenceslao Shaw CortezPacific Northwest National LaboratoryE-mail megerősítve itt: pnnl.gov
Miroslav FikarProfessor, Slovak University of Technology in BratislavaE-mail megerősítve itt: stuba.sk
James KochData Scientist, Pacific Northwest National LaboratoryE-mail megerősítve itt: pnnl.gov
Gerald SchweigerProfessor (Full) Vienna University of TechnologyE-mail megerősítve itt: tugraz.at
Stefano Di CairanoDeputy Director, Distinguished Research Scientist, Mitsubishi Electric ResearchE-mail megerősítve itt: ieee.org
Shrirang AbhyankarSenior Scientist, Pacific Northwest National LaboratoryE-mail megerősítve itt: pnnl.gov
Colin JonesAssociate Professor of Engineering, École Polytechnique Fédérale de Lausanne (EPFL)E-mail megerősítve itt: epfl.ch
Truong X. NghiemUniversity of Central FloridaE-mail megerősítve itt: ucf.edu
Bing DongProfessor, Ph.D. IBPSA Fellow. Mechanical and Aerospace Engineering, Syracuse UniversityE-mail megerősítve itt: syr.edu
Salvatore CarlucciFull professor, University of InsubriaE-mail megerősítve itt: uninsubria.it
Lawrence PileggiCoraluppi Head and Tanoto Professor of ECE, Carnegie Mellon UniversityE-mail megerősítve itt: andrew.cmu.edu
Zoltan NagyUniversity of Texas at AustinE-mail megerősítve itt: utexas.edu

Követés

Jan Drgona

Pacific Northwest National Laboratory, Richland, WA, United States

E-mail megerősítve itt: pnnl.gov - Kezdőlap

scientific machine learning differentiable programming optimal control sustainable energy


Cím Rendezés hivatkozások szerint Rendezés év szerint Rendezés cím szerint	Hivatkozott rá Hivatkozott rá	Év
All you need to know about model predictive control for buildings J Drgoňa, J Arroyo, IC Figueroa, D Blum, K Arendt, D Kim, EP Ollé, ... Annual Reviews in Control 50, 190-232, 2020	766	2020
Approximate model predictive building control via machine learning J Drgoňa, D Picard, M Kvasnica, L Helsen Applied energy 218, 199-216, 2018	290	2018
Physics-constrained deep learning of multi-zone building thermal dynamics J Drgoňa, AR Tuor, V Chandan, DL Vrabie Energy and Buildings 243, 110992, 2021	136	2021
Building optimization testing framework (BOPTEST) for simulation-based benchmarking of control strategies in buildings D Blum, J Arroyo, S Huang, J Drgoňa, F Jorissen, HT Walnum, Y Chen, ... Journal of Building Performance Simulation 14 (5), 586-610, 2021	127	2021
Cloud-based implementation of white-box model predictive control for a GEOTABS office building: A field test demonstration J Drgoňa, D Picard, L Helsen Journal of Process Control 88, 63-77, 2020	115	2020
Impact of the controller model complexity on model predictive control performance for buildings D Picard, J Drgoňa, M Kvasnica, L Helsen Energy and Buildings 152, 739-751, 2017	103	2017
Constructing neural network based models for simulating dynamical systems C Legaard, T Schranz, G Schweiger, J Drgoňa, B Falay, C Gomes, ... ACM Computing Surveys 55 (11), 1-34, 2023	102	2023
Differentiable predictive control: Deep learning alternative to explicit model predictive control for unknown nonlinear systems J Drgoňa, K Kiš, A Tuor, D Vrabie, M Klaučo Journal of Process Control 116, 80-92, 2022	73*	2022
Ten questions concerning reinforcement learning for building energy management Z Nagy, G Henze, S Dey, J Arroyo, L Helsen, X Zhang, B Chen, ... Building and Environment 241, 110435, 2023	63	2023
Learning constrained parametric differentiable predictive control policies with guarantees J Drgoňa, A Tuor, D Vrabie IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2024	46*	2024
Physics-informed machine learning for modeling and control of dynamical systems TX Nghiem, J Drgoňa, C Jones, Z Nagy, R Schwan, B Dey, A Chakrabarty, ... 2023 American Control Conference (ACC), 3735-3750, 2023	43	2023
Optimal control of a laboratory binary distillation column via regionless explicit MPC J Drgoňa, M Klaučo, F Janeček, M Kvasnica Computers & Chemical Engineering 96, 139-148, 2017	40	2017
Explicit Stochastic MPC Approach to Building Temperature Control J. Drgoňa, – M. Kvasnica, – M. Klaučo, – M. Fikar V IEEE Conference on Decision and Control, 6440–6445, 2013	38*	2013
Constrained neural ordinary differential equations with stability guarantees A Tuor, J Drgona, D Vrabie arXiv preprint arXiv:2004.10883, 2020	37	2020
A guideline to document occupant behavior models for advanced building controls B Dong, R Markovic, S Carlucci, Y Liu, A Wagner, A Liguori, C van Treeck, ... Building and Environment 219, 109195, 2022	36	2022
Neural ordinary differential equations for nonlinear system identification A Rahman, J Drgoňa, A Tuor, J Strube 2022 American control conference (ACC), 3979-3984, 2022	32	2022
Deep learning explicit differentiable predictive control laws for buildings J Drgoňa, A Tuor, E Skomski, S Vasisht, D Vrabie IFAC-PapersOnLine 54 (6), 14-19, 2021	31	2021
MPC-based reference governor control of a continuous stirred-tank reactor J Holaza, M Klaučo, J Drgoňa, J Oravec, M Kvasnica, M Fikar Computers & Chemical Engineering 108, 289-299, 2018	31	2018
NeuroMANCER: Neural Modules with Adaptive Nonlinear Constraints and Efficient Regularizations J Drgona, A Tuor, J Koch, M Shapiro, D Vrabie URL https://github. com/pnnl/neuromancer, 2023	30*	2023
Building Temperature Control by Simple MPC-like Feedback Laws Learned from Closed-Loop Data. S Klaučo, M. – Drgoňa, J. – Kvasnica, M. – Di Cairano V Preprints of the 19th IFAC World Congress Cape Town (South Africa), 581–586, 2014	27*	2014

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