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ORCIDJohn Lygeros
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- affiliation: ETH Zurich, Switzerland
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2020 – today
- 2023
[j118]Jeremy Coulson
, Henk J. van Waarde, John Lygeros, Florian Dörfler:
A Quantitative Notion of Persistency of Excitation and the Robust Fundamental Lemma. IEEE Control. Syst. Lett. 7: 1243-1248 (2023)- [j117]Mohammad Khosravi, Christopher König, Markus Maier, Roy S. Smith, John Lygeros, Alisa Rupenyan:
Safety-Aware Cascade Controller Tuning Using Constrained Bayesian Optimization. IEEE Trans. Ind. Electron. 70(2): 2128-2138 (2023) - [i112]Xavier Guidetti, Efe C. Balta, Yannick Nagel, Hang Yin, Alisa Rupenyan, John Lygeros:
Stress Flow Guided Non-Planar Print Trajectory Optimization for Additive Manufacturing of Anisotropic Polymers. CoRR abs/2301.04999 (2023) - 2022
- [j116]Andrea Martinelli, Matilde Gargiani, John Lygeros:
Data-driven optimal control with a relaxed linear program. Autom. 136: 110052 (2022) - [j115]Mohammad H. Mamduhi, Efe C. Balta, Alisa Rupenyan, John Lygeros:
Information-Operation Technology Integration in Industrial Cyberphysical Systems. Computer 55(11): 115-118 (2022) - [j114]Sandeep Menta, Joseph Warrington, John Lygeros, Manfred Morari:
Learning Q-Function Approximations for Hybrid Control Problems. IEEE Control. Syst. Lett. 6: 1364-1369 (2022) - [j113]Dominic Liao-McPherson, Efe C. Balta, Alisa Rupenyan, John Lygeros:
On Robustness in Optimization-Based Constrained Iterative Learning Control. IEEE Control. Syst. Lett. 6: 2846-2851 (2022) - [j112]Matilde Gargiani, Andrea Zanelli, Dominic Liao-McPherson, Tyler H. Summers, John Lygeros:
Dynamic Programming Through the Lens of Semismooth Newton-Type Methods. IEEE Control. Syst. Lett. 6: 2996-3001 (2022) - [j111]Andrea Martinelli, Matilde Gargiani, Marina Draskovic, John Lygeros:
Data-Driven Optimal Control of Affine Systems: A Linear Programming Perspective. IEEE Control. Syst. Lett. 6: 3092-3097 (2022) - [j110]Carlo Cenedese, Patrick Stokkink, Nikolas Geroliminis, John Lygeros:
Incentive-based electric vehicle charging for managing bottleneck congestion. Eur. J. Control 68: 100697 (2022) - [j109]Xavier Guidetti, Alisa Rupenyan, Lutz Fassl, Majid Nabavi, John Lygeros:
Advanced Manufacturing Configuration by Sample-Efficient Batch Bayesian Optimization. IEEE Robotics Autom. Lett. 7(4): 11886-11893 (2022) - [j108]Paul Nathaniel Beuchat, Joseph Warrington, John Lygeros:
Accelerated Point-Wise Maximum Approach to Approximate Dynamic Programming. IEEE Trans. Autom. Control. 67(1): 251-266 (2022) - [j107]Jeremy Coulson, John Lygeros, Florian Dörfler:
Distributionally Robust Chance Constrained Data-Enabled Predictive Control. IEEE Trans. Autom. Control. 67(7): 3289-3304 (2022) - [j106]Ahmed Aboudonia, Annika Eichler, Francesco Cordiano, Goran Banjac, John Lygeros:
Distributed Model Predictive Control With Reconfigurable Terminal Ingredients for Reference Tracking. IEEE Trans. Autom. Control. 67(11): 6263-6270 (2022) - [j105]Linbin Huang, Jeremy Coulson, John Lygeros, Florian Dörfler:
Decentralized Data-Enabled Predictive Control for Power System Oscillation Damping. IEEE Trans. Control. Syst. Technol. 30(3): 1065-1077 (2022) - [j104]Mohammad Khosravi, Varsha Behrunani, Piotr Myszkorowski, Roy S. Smith, Alisa Rupenyan, John Lygeros:
Performance-Driven Cascade Controller Tuning With Bayesian Optimization. IEEE Trans. Ind. Electron. 69(1): 1032-1042 (2022) - [c224]Ahmed Aboudonia, Andrea Martinelli, Nicolas Hoischen, John Lygeros:
Reconfigurable Plug-and-play Distributed Model Predictive Control for Reference Tracking. CDC 2022: 1130-1135 - [c223]Efe C. Balta, Andrea Iannelli, Roy S. Smith, John Lygeros:
Regret Analysis of Online Gradient Descent-based Iterative Learning Control with Model Mismatch. CDC 2022: 1479-1484 - [c222]Marta Fochesato, Carlo Cenedese, John Lygeros:
A Stackelberg game for incentive-based demand response in energy markets. CDC 2022: 2487-2492 - [c221]Benjamin Gravell, Matilde Gargiani, John Lygeros, Tyler H. Summers:
Policy Iteration for Multiplicative Noise Output Feedback Control. CDC 2022: 2967-2972 - [c220]Marta Fochesato, John Lygeros:
Data-Driven Distributionally Robust Bounds for Stochastic Model Predictive Control. CDC 2022: 3611-3616 - [c219]Alberto Padoan, Jeremy Coulson, Henk J. van Waarde, John Lygeros, Florian Dörfler:
Behavioral uncertainty quantification for data-driven control. CDC 2022: 4726-4731 - [c218]Francesco Micheli, Tyler H. Summers, John Lygeros:
Data-driven distributionally robust MPC for systems with uncertain dynamics. CDC 2022: 4788-4793 - [c217]Aren Karapetyan, Andrea Iannelli, John Lygeros:
On the Regret of H∞ Control. CDC 2022: 6181-6186 - [c216]Carlo Cenedese, Michele Cucuzzella, Antonella Ferrara, John Lygeros:
A Novel Control-Oriented Cell Transmission Model Including Service Stations on Highways. CDC 2022: 6278-6283 - [c215]Francesco Micheli, John Lygeros:
Scenario-based Stochastic MPC for systems with uncertain dynamics. ECC 2022: 833-838 - [c214]Ahmed Aboudonia, Goran Banjac, Annika Eichler, John Lygeros:
Online Computation of Terminal Ingredients in Distributed Model Predictive Control for Reference Tracking. ECC 2022: 847-852 - [c213]Riccardo Zuliani, Efe C. Balta, Alisa Rupenyan, John Lygeros:
Batch Model Predictive Control for Selective Laser Melting. ECC 2022: 1560-1565 - [c212]Dominic Liao-McPherson, Efe C. Balta, Ryan Wüest, Alisa Rupenyan, John Lygeros:
In-layer Thermal Control of a Multi-layer Selective Laser Melting Process. ECC 2022: 1678-1683 - [c211]Matilde Gargiani, Andrea Zanelli, Andrea Martinelli, Tyler H. Summers, John Lygeros:
PAGE-PG: A Simple and Loopless Variance-Reduced Policy Gradient Method with Probabilistic Gradient Estimation. ICML 2022: 7223-7240 - [c210]Efe C. Balta, Mohammad H. Mamduhi, John Lygeros, Alisa Rupenyan:
Controller-Aware Dynamic Network Management for Industry 4.0. IECON 2022: 1-6 - [c209]Andrea Martin, Luca Furieri, Florian Dörfler, John Lygeros, Giancarlo Ferrari-Trecate:
Safe Control with Minimal Regret. L4DC 2022: 726-738 - [i111]Angeliki Kamoutsi, Goran Banjac, John Lygeros:
Stochastic convex optimization for provably efficient apprenticeship learning. CoRR abs/2201.00039 (2022) - [i110]Matilde Gargiani, Andrea Zanelli, Andrea Martinelli, Tyler H. Summers, John Lygeros:
PAGE-PG: A Simple and Loopless Variance-Reduced Policy Gradient Method with Probabilistic Gradient Estimation. CoRR abs/2202.00308 (2022) - [i109]Andrea Martin, Luca Furieri, Florian Dörfler, John Lygeros, Giancarlo Ferrari-Trecate:
Safe Control with Minimal Regret. CoRR abs/2203.00358 (2022) - [i108]Dominic Liao-McPherson, Efe C. Balta, Alisa Rupenyan, John Lygeros:
On Robustness in Optimization-Based Constrained Iterative Learning Control. CoRR abs/2203.05291 (2022) - [i107]Andrea Martinelli, Matilde Gargiani, Marina Draskovic, John Lygeros:
Data-driven optimal control of affine systems: A linear programming perspective. CoRR abs/2203.12044 (2022) - [i106]Aren Karapetyan, Andrea Iannelli, John Lygeros:
On the Regret of H∞ control. CoRR abs/2203.16237 (2022) - [i105]Benjamin Gravell, Matilde Gargiani, John Lygeros, Tyler H. Summers:
Policy Iteration for Multiplicative Noise Output Feedback Control. CoRR abs/2203.17165 (2022) - [i104]Alberto Padoan, Jeremy Coulson, Henk J. van Waarde, John Lygeros, Florian Dörfler:
Behavioral uncertainty quantification for data-driven control. CoRR abs/2204.02671 (2022) - [i103]Efe C. Balta, Andrea Iannelli, Roy S. Smith, John Lygeros:
Regret Analysis of Online Gradient Descent-based Iterative Learning Control with Model Mismatch. CoRR abs/2204.04722 (2022) - [i102]Marta Fochesato, Carlo Cenedese, John Lygeros:
A Stackelberg game for incentive-based demand response in energy markets. CoRR abs/2204.08730 (2022) - [i101]Xavier Guidetti, Alisa Rupenyan, Lutz Fassl, Majid Nabavi, John Lygeros:
Advanced Manufacturing Configuration by Sample-efficient Batch Bayesian Optimization. CoRR abs/2205.11827 (2022) - [i100]Efe C. Balta, Mohammad H. Mamduhi, John Lygeros, Alisa Rupenyan:
Controller-Aware Dynamic Network Management for Industry 4.0. CoRR abs/2205.14449 (2022) - [i99]Carlo Cenedese, Michele Cucuzzella, Antonella Ferrara, John Lygeros:
A Novel Control-Oriented Cell Transition Model Including Service Stations on Highways. CoRR abs/2205.15115 (2022) - [i98]Samuel Balula, Dominic Liao-McPherson, Alisa Rupenyan, John Lygeros:
Data-driven Reference Trajectory Optimization for Precision Motion Systems. CoRR abs/2205.15694 (2022) - [i97]Linbin Huang, John Lygeros, Florian Dörfler:
Robust and Kernelized Data-Enabled Predictive Control for Nonlinear Systems. CoRR abs/2206.01866 (2022) - [i96]Ahmed Aboudonia, Goran Banjac, Annika Eichler, John Lygeros:
Online Computation of Terminal Ingredients in Distributed Model Predictive Control for Reference Tracking. CoRR abs/2207.09216 (2022) - [i95]Ahmed Aboudonia, Andrea Martinelli, Nicolas Hoischen, John Lygeros:
Reconfigurable Plug-and-play Distributed Model Predictive Control for Reference Tracking. CoRR abs/2207.09233 (2022) - [i94]Milos Katanic, John Lygeros, Gabriela Hug:
Moving-Horizon State Estimation for Power Networks and Synchronous Generators. CoRR abs/2207.12150 (2022) - [i93]Ezzat Elokda, Carlo Cenedese, Kenan Zhang, John Lygeros, Florian Dörfler:
CARMA: Fair and efficient bottleneck congestion management with karma. CoRR abs/2208.07113 (2022) - [i92]Francesco Micheli, Tyler H. Summers, John Lygeros:
Data-driven distributionally robust MPC for systems with uncertain dynamics. CoRR abs/2209.08869 (2022) - [i91]Xavier Guidetti, Marino Kühne, Yannick Nagel, Efe C. Balta, Alisa Rupenyan, John Lygeros:
Data-Driven Process Optimization of Fused Filament Fabrication based on In Situ Measurements. CoRR abs/2210.15239 (2022) - [i90]Yuchao Li, Aren Karapetyan, John Lygeros, Karl Henrik Johansson, Jonas Mårtensson:
Performance Bounds of Model Predictive Control for Unconstrained and Constrained Linear Quadratic Problems and Beyond. CoRR abs/2211.06187 (2022) - [i89]Giuseppe Belgioioso, Dominic Liao-McPherson, Mathias Hudoba de Badyn, Nicolas Pelzmann, John Lygeros, Florian Dörfler:
Stability and Robustness of Distributed Suboptimal Model Predictive Control. CoRR abs/2211.07341 (2022) - [i88]Andrea Martin, Luca Furieri, Florian Dörfler, John Lygeros, Giancarlo Ferrari-Trecate:
Follow the Clairvoyant: an Imitation Learning Approach to Optimal Control. CoRR abs/2211.07389 (2022) - [i87]Aren Karapetyan, Anastasios Tsiamis, Efe C. Balta, Andrea Iannelli, John Lygeros:
Implications of Regret on Stability of Linear Dynamical Systems. CoRR abs/2211.07411 (2022) - [i86]Niklas Schmid, John Lygeros:
Probabilistic Reachability and Invariance Computation of Stochastic Systems using Linear Programming. CoRR abs/2211.07544 (2022) - [i85]Samuel Balula, Dominic Liao-McPherson, Stefan Stevsic, Alisa Rupenyan, John Lygeros:
Drone-based Volume Estimation in Indoor Environments. CoRR abs/2211.08013 (2022) - [i84]Carlo Cenedese, Michele Cucuzzella, Adriano Cotta Ramusino, Davide Spalenza, John Lygeros, Antonella Ferrara:
Optimal service station design for traffic mitigation via genetic algorithm and neural network. CoRR abs/2211.10159 (2022) - 2021
- [j103]Ahmed Aboudonia, Andrea Martinelli, John Lygeros:
Passivity-Based Decentralized Control for Discrete-Time Large-Scale Systems. IEEE Control. Syst. Lett. 5(6): 2072-2077 (2021) - [j102]George J. Pappas, Kostas Daniilidis, Leonidas J. Guibas, Lydia E. Kavraki, Petros Koumoutsakos, Kostas J. Kyriakopoulos, John Lygeros, Michael S. Triantafyllou, Panagiotis Tsiotras:
Robotics in the AI era: A vision for a Hellenic Robotics Initiative. Found. Trends Robotics 9(3): 201-265 (2021) - [j101]Goran Banjac, John Lygeros:
On the asymptotic behavior of the Douglas-Rachford and proximal-point algorithms for convex optimization. Optim. Lett. 15(8): 2719-2732 (2021) - [j100]Dimitris Gkouletsos, Andrea Iannelli, Mathias Hudoba de Badyn, John Lygeros:
Decentralized Trajectory Optimization for Multi-Agent Ergodic Exploration. IEEE Robotics Autom. Lett. 6(4): 6329-6336 (2021) - [j99]Felix Rey, Peter Hokayem, John Lygeros:
ADMM for Exploiting Structure in MPC Problems. IEEE Trans. Autom. Control. 66(5): 2076-2086 (2021) - [j98]Basilio Gentile, Dario Paccagnan, Bolutife Ogunsula, John Lygeros:
The Nash Equilibrium With Inertia in Population Games. IEEE Trans. Autom. Control. 66(12): 5742-5755 (2021) - [j97]Benjamin Flamm, Annika Eichler, Joseph Warrington, John Lygeros:
Two-Stage Dual Dynamic Programming With Application to Nonlinear Hydro Scheduling. IEEE Trans. Control. Syst. Technol. 29(1): 96-107 (2021) - [c208]Ahmed Aboudonia, Andrea Martinelli, John Lygeros:
Passivity-based Decentralized Control for Discrete-time Large-scale Systems. ACC 2021: 2037-2042 - [c207]Xavier Guidetti, Alisa Rupenyan, Lutz Fassl, Majid Nabavi, John Lygeros:
Plasma Spray Process Parameters Configuration using Sample-efficient Batch Bayesian Optimization. CASE 2021: 31-38 - [c206]Anilkumar Parsi, Ahmed Aboudonia, Andrea Iannelli, John Lygeros, Roy S. Smith:
A distributed framework for linear adaptive MPC. CDC 2021: 460-465 - [c205]Alisa Rupenyan, Mohammad Khosravi, John Lygeros:
Performance-based Trajectory Optimization for Path Following Control Using Bayesian Optimization. CDC 2021: 2116-2121 - [c204]Giuseppe Belgioioso, Dominic Liao-McPherson, Mathias Hudoba de Badyn, Saverio Bolognani, John Lygeros, Florian Dörfler:
Sampled-Data Online Feedback Equilibrium Seeking: Stability and Tracking. CDC 2021: 2702-2708 - [c203]Mathias Hudoba de Badyn, Erik Miehling, Dylan Janak, Behçet Açikmese, Mehran Mesbahi, Tamer Basar, John Lygeros, Roy S. Smith:
Discrete-Time Linear-Quadratic Regulation via Optimal Transport. CDC 2021: 3060-3065 - [c202]Efe C. Balta, Kira Barton, Dawn M. Tilbury, Alisa Rupenyan, John Lygeros:
Learning-Based Repetitive Precision Motion Control with Mismatch Compensation. CDC 2021: 3605-3610 - [c201]Andrea Martinelli, Matilde Gargiani, John Lygeros:
On the Synthesis of Bellman Inequalities for Data-Driven Optimal Control. CDC 2021: 4352-4357 - [c200]Angeliki Kamoutsi, Goran Banjac, John Lygeros:
Efficient Performance Bounds for Primal-Dual Reinforcement Learning from Demonstrations. ICML 2021: 5257-5268 - [c199]Eugenio Chisari, Alexander Liniger, Alisa Rupenyan, Luc Van Gool, John Lygeros:
Learning from Simulation, Racing in Reality. ICRA 2021: 8046-8052 - [c198]Christopher König, Matteo Turchetta, John Lygeros, Alisa Rupenyan, Andreas Krause:
Safe and Efficient Model-free Adaptive Control via Bayesian Optimization. ICRA 2021: 9782-9788 - [c197]Ali Jadbabaie, John Lygeros, George J. Pappas, Pablo A. Parrilo, Benjamin Recht, Claire J. Tomlin, Melanie N. Zeilinger:
Preface. L4DC 2021: 1-5 - [c196]Felix Bünning, Adrian Schalbetter, Ahmed Aboudonia, Mathias Hudoba de Badyn, Philipp Heer, John Lygeros:
Input Convex Neural Networks for Building MPC. L4DC 2021: 251-262 - [e2]Ali Jadbabaie, John Lygeros, George J. Pappas, Pablo A. Parrilo, Benjamin Recht, Claire J. Tomlin, Melanie N. Zeilinger:
Proceedings of the 3rd Annual Conference on Learning for Dynamics and Control, L4DC 2021, 7-8 June 2021, Virtual Event, Switzerland. Proceedings of Machine Learning Research 144, PMLR 2021 [contents] - [i83]Christopher König, Matteo Turchetta, John Lygeros, Alisa Rupenyan, Andreas Krause:
Safe and Efficient Model-free Adaptive Control via Bayesian Optimization. CoRR abs/2101.07825 (2021) - [i82]Xavier Guidetti, Alisa Rupenyan, Lutz Fassl, Majid Nabavi, John Lygeros:
Sample-efficient Plasma Spray Process Configuration with Constrained Bayesian Optimization. CoRR abs/2103.13881 (2021) - [i81]Alisa Rupenyan, Mohammad Khosravi, John Lygeros:
Performance-based Trajectory Optimization for Path Following Control Using Bayesian Optimization. CoRR abs/2103.15416 (2021) - [i80]Linbin Huang, Jianzhe Zhen, John Lygeros, Florian Dörfler:
Robust Data-Enabled Predictive Control: Tractable Formulations and Performance Guarantees. CoRR abs/2105.07199 (2021) - [i79]Ahmed Aboudonia, Andrea Martinelli, John Lygeros:
Passivity-based Decentralized Control for Discrete-time Large-scale Systems. CoRR abs/2107.07277 (2021) - [i78]Anilkumar Parsi, Ahmed Aboudonia, Andrea Iannelli, John Lygeros, Roy S. Smith:
A distributed framework for linear adaptive MPC. CoRR abs/2109.05777 (2021) - [i77]Andrea Martinelli, Matilde Gargiani, John Lygeros:
On the Synthesis of Bellman Inequalities for Data-Driven Optimal Control. CoRR abs/2109.13193 (2021) - [i76]Nicolas Lefebure, Mohammad Khosravi, Mathias Hudoba de Badyn, Felix Bünning, John Lygeros, Colin N. Jones, Roy S. Smith:
Distributed Model Predictive Control of Buildings and Energy Hubs. CoRR abs/2110.01734 (2021) - [i75]Felix Bünning, Benjamin Huber, Adrian Schalbetter, Ahmed Aboudonia, Mathias Hudoba de Badyn, Philipp Heer, Roy S. Smith, John Lygeros:
Physics-informed linear regression is a competitive approach compared to Machine Learning methods in building MPC. CoRR abs/2110.15911 (2021) - [i74]Dominic Liao-McPherson, Efe C. Balta, Ryan Wüest, Alisa Rupenyan, John Lygeros:
In-layer Thermal Control of a Multi-layer Selective Laser Melting Process. CoRR abs/2111.00890 (2021) - [i73]Riccardo Zuliani, Efe C. Balta, Alisa Rupenyan, John Lygeros:
Batch Model Predictive Control for Selective Laser Melting. CoRR abs/2111.08363 (2021) - [i72]Efe C. Balta, Kira Barton, Dawn M. Tilbury, Alisa Rupenyan, John Lygeros:
Learning-Based Repetitive Precision Motion Control with Mismatch Compensation. CoRR abs/2111.10246 (2021) - [i71]Angeliki Kamoutsi, Goran Banjac, John Lygeros:
Efficient Performance Bounds for Primal-Dual Reinforcement Learning from Demonstrations. CoRR abs/2112.14004 (2021) - 2020
- [j96]Francesca Parise, Sergio Grammatico, Basilio Gentile, John Lygeros:
Distributed convergence to Nash equilibria in network and average aggregative games. Autom. 117: 108959 (2020) - [j95]Daniele Alpago, Florian Dörfler, John Lygeros:
An Extended Kalman Filter for Data-Enabled Predictive Control. IEEE Control. Syst. Lett. 4(4): 994-999 (2020) - [j94]Marc Hohmann, Joseph Warrington, John Lygeros:
A moment and sum-of-squares extension of dual dynamic programming with application to nonlinear energy storage problems. Eur. J. Oper. Res. 283(1): 16-32 (2020) - [j93]Juraj Kabzan, Miguel de la Iglesia Valls, Victor J. F. Reijgwart, Hubertus Franciscus Cornelis Hendrikx, Claas Ehmke, Manish Prajapat, Andreas Bühler, Nikhil Bharadwaj Gosala, Mehak Gupta, Ramya Sivanesan, Ankit Dhall, Eugenio Chisari, Napat Karnchanachari, Sonja Brits, Manuel Dangel, Inkyu Sa, Renaud Dubé, Abel Gawel, Mark Pfeiffer, Alexander Liniger, John Lygeros, Roland Siegwart:
AMZ Driverless: The full autonomous racing system. J. Field Robotics 37(7): 1267-1294 (2020) - [j92]Michel Schubiger, Goran Banjac, John Lygeros:
GPU acceleration of ADMM for large-scale quadratic programming. J. Parallel Distributed Comput. 144: 55-67 (2020) - [j91]Paul Nathaniel Beuchat, Angelos Georghiou, John Lygeros:
Performance Guarantees for Model-Based Approximate Dynamic Programming in Continuous Spaces. IEEE Trans. Autom. Control. 65(1): 143-158 (2020) - [j90]Georgios Darivianakis, Annika Eichler, John Lygeros:
Distributed Model Predictive Control for Linear Systems With Adaptive Terminal Sets. IEEE Trans. Autom. Control. 65(3): 1044-1056 (2020) - [j89]Francesca Parise, Basilio Gentile, John Lygeros:
A Distributed Algorithm For Almost-Nash Equilibria of Average Aggregative Games With Coupling Constraints. IEEE Trans. Control. Netw. Syst. 7(2): 770-782 (2020) - [j88]Alexander Liniger, John Lygeros:
A Noncooperative Game Approach to Autonomous Racing. IEEE Trans. Control. Syst. Technol. 28(3): 884-897 (2020) - [c195]Alexandros Tanzanakis, John Lygeros:
Constrained Optimal Tracking Control of Unknown Systems: A Multi-Step Linear Programming Approach. CDC 2020: 2455-2462 - [c194]Samuel Balula, Alexander Liniger, Alisa Rupenyan, John Lygeros:
Reference design for closed loop system optimization. ECC 2020: 650-655 - [c193]José L. Vázquez, Marius Brühlmeier, Alexander Liniger, Alisa Rupenyan, John Lygeros:
Optimization-Based Hierarchical Motion Planning for Autonomous Racing. IROS 2020: 2397-2403 - [c192]Sandeep Menta, Joseph Warrington, John Lygeros, Manfred Morari:
Learning solutions to hybrid control problems using Benders cuts. L4DC 2020: 118-126 - [i70]Alexandros Tanzanakis, John Lygeros:
Data-Driven Control of Unknown Systems: A Linear Programming Approach. CoRR abs/2003.00779 (2020) - [i69]Samuel Balula, Alexander Liniger, Alisa Rupenyan, John Lygeros:
Reference design for closed loop system optimization. CoRR abs/2003.01429 (2020) - [i68]José L. Vázquez, Marius Brühlmeier, Alexander Liniger, Alisa Rupenyan, John Lygeros:
Optimization-Based Hierarchical Motion Planning for Autonomous Racing. CoRR abs/2003.04882 (2020) - [i67]Andrea Martinelli, John Lygeros:
Learning Optimal Control Policies for Stochastic Systems with a Relaxed Bellman Operator. CoRR abs/2003.08721 (2020) - [i66]Andrea Martinelli, John Lygeros:
Control of Networked Systems by Clustering: The Degree of Freedom Concept. CoRR abs/2004.10153 (2020) - [i65]Mohammad Khosravi, Varsha Behrunani, Roy S. Smith, Alisa Rupenyan, John Lygeros:
Cascade Control: Data-Driven Tuning Approach Based on Bayesian Optimization. CoRR abs/2005.03970 (2020) - [i64]Ahmed Aboudonia, Annika Eichler, John Lygeros:
Distributed Model Predictive Control with Asymmetric Adaptive Terminal Sets for the Regulation of Large-scale Systems. CoRR abs/2005.04077 (2020) - [i63]