Draguna Vrabie

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F.L. Lewisprofessor of electrical engineering, The University of Texas at ArlingtonPatvirtintas el. paštas uta.edu
Jan DrgonaJohns Hopkins UniversityPatvirtintas el. paštas jh.edu
Sen HuangOak Ridge National LaboratoryPatvirtintas el. paštas ornl.gov
Kyriakos G. VamvoudakisDutton-Ducoffe Endowed Professor, School of Aerospace Engineering, Georgia Institute of TechnologyPatvirtintas el. paštas gatech.edu
Aaron TuorWestern Washington UniversityPatvirtintas el. paštas pnnl.gov
Helsen LieveProfessor of Mechanical Engineering, KU LeuvenPatvirtintas el. paštas mech.kuleuven.be
Michael WetterLBNL, Berkeley, CAPatvirtintas el. paštas lbl.gov
Murad Abu-KhalafMassachusetts Institute of TechnologyPatvirtintas el. paštas csail.mit.edu
Yan ChenPacific Northwest National LaboratoryPatvirtintas el. paštas pnnl.gov
David H. BlumComputational Research Scientist/Engineer, Lawrence Berkeley National LaboratoryPatvirtintas el. paštas lbl.gov
Vassilis SyrmosUniversity of HawaiiPatvirtintas el. paštas hawaii.edu
Javier ArroyoWedocoPatvirtintas el. paštas wedoco.io
Wangda ZuoProfessor, Pennsylvania State UniversityPatvirtintas el. paštas psu.edu
Arnab BhattacharyaPacific Northwest National LaboratoryPatvirtintas el. paštas pnnl.gov
Vikas ChandanSenior Scientist, CrossnokayePatvirtintas el. paštas crossnokaye.com
Soumya VasishtPacific Northwest National Laboratory | University of WashingtonPatvirtintas el. paštas uw.edu
Saptarshi BhattacharyaStaff Scientist, Pacific Northwest National LaboratoryPatvirtintas el. paštas pnnl.gov
Octavian PastravanuTechnical University "Gh. Asachi" of Iasi, RomaniaPatvirtintas el. paštas ac.tuiasi.ro
Soumya KunduPacific Northwest National Laboratory, University of Vermont, Washington State UniversityPatvirtintas el. paštas pnnl.gov
Piljae ImOak Ridge National LaboratoryPatvirtintas el. paštas ornl.gov

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Draguna Vrabie

Pacific Northwest National Laboratory

Patvirtintas el. paštas pnnl.gov

Control Systems and Machine Learning


Pavadinimas Rūšiuoti pagal šaltinius Rūšiuoti pagal metus Rūšiuoti pagal pavadinimą	Cituota Cituota	Metai
Optimal control (hardback) FL LEWIS, D VRABIE, VL SYRMOS	6617*	2012
Reinforcement learning and adaptive dynamic programming for feedback control FL Lewis, D Vrabie Circuits and Systems Magazine, IEEE 9 (3), 32-50, 2009	1651	2009
Reinforcement learning and feedback control: Using natural decision methods to design optimal adaptive controllers FL Lewis, D Vrabie, KG Vamvoudakis IEEE Control Systems Magazine 32 (6), 76-105, 2012	1136	2012
Adaptive optimal control for continuous-time linear systems based on policy iteration D Vrabie, O Pastravanu, M Abu-Khalaf, FL Lewis Automatica 45 (2), 477-484, 2009	947	2009
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	769	2020
Neural network approach to continuous-time direct adaptive optimal control for partially unknown nonlinear systems D Vrabie, F Lewis Neural Networks 22 (3), 237-246, 2009	700	2009
Optimal adaptive control and differential games by reinforcement learning principles D Vrabie, KG Vamvoudakis, FL Lewis Inst of Engineering & Technology, 2012	387	2012
Online adaptive algorithm for optimal control with integral reinforcement learning KG Vamvoudakis, D Vrabie, FL Lewis International Journal of Robust and Nonlinear Control 24 (17), 2686-2710, 2014	174	2014
Adaptive dynamic programming for online solution of a zero-sum differential game D Vrabie, F Lewis Journal of Control Theory and Applications 9, 353-360, 2011	155	2011
Physics-constrained deep learning of multi-zone building thermal dynamics J Drgoňa, AR Tuor, V Chandan, DL Vrabie Energy and Buildings 243, 110992, 2021	138	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
Sensor impacts on building and HVAC controls: A critical review for building energy performance Y Bae, S Bhattacharya, B Cui, S Lee, Y Li, L Zhang, P Im, V Adetola, ... Advances in Applied Energy 4, 100068, 2021	111	2021
Integral Reinforcement Learning for online computation of feedback Nash strategies of nonzero-sum differential games D Vrabie, F Lewis Decision and Control (CDC), 2010 49th IEEE Conference on, 3066-3071, 2010	71	2010
Adaptive optimal controllers based on generalized policy iteration in a continuous-time framework D Vrabie, K Vamvoudakis, F Lewis 2009 17th Mediterranean Conference on Control and Automation, 1402-1409, 2009	71	2009
Adaptive optimal control algorithm for continuous-time nonlinear systems based on policy iteration D Vrabie, FL Lewis 2008 47th IEEE Conference on Decision and Control, 73-79, 2008	66	2008
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, 110435, 2023	65	2023
Parameter estimation of a building system model and impact of estimation error on closed-loop performance S Bengea, V Adetola, K Kang, MJ Liba, D Vrabie, R Bitmead, ... 2011 50th IEEE Conference on Decision and Control and European Control …, 2011	62	2011
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	60	2022
Simulation and experimental demonstration of model predictive control in a building HVAC system P Li, D Vrabie, D Li, SC Bengea, S Mijanovic, ZD O’Neill Science and Technology for the Built Environment 21 (6), 721-732, 2015	51	2015
Continuous-time ADP for linear systems with partially unknown dynamics D Vrabie, M Abu-Khalaf, FL Lewis, Y Wang 2007 IEEE International Symposium on Approximate Dynamic Programming and …, 2007	50	2007

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