Control
If it moves, we control it.
Our expertise in this area covers multivariable, nonlinear, optimal and model-predictive control theory, nonlinear estimation, nonlinear dynamical systems, and mechanical design. We conduct both fundamental and applied research targeting a wide range of applications including autonomous driving, factory automation and HVAC systems.
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Researchers
Stefano
Di Cairano
Yebin
Wang
Avishai
Weiss
Scott A.
Bortoff
Christopher R.
Laughman
Abraham P.
Vinod
Daniel N.
Nikovski
Arvind
Raghunathan
Vedang M.
Deshpande
Abraham
Goldsmith
Philip V.
Orlik
William S.
Yerazunis
Purnanand
Elango
Hongtao
Qiao
Chungwei
Lin
Jianlin
Guo
Toshiaki
Koike-Akino
Yanting
Ma
Matthew
Brand
Dehong
Liu
Alexander
Schperberg
Nobuyuki
Yoshikawa
Jordan
Leung
Pedro
Miraldo
Bingnan
Wang
Ye
Wang
Gordon
Wichern
Petros T.
Boufounos
Hassan
Mansour
Kento
Tomita
Jinyun
Zhang
Siddarth
Jain
Jing
Liu
Saviz
Mowlavi
Kieran
Parsons
Zhaolin
Ren
Hongbo
Sun
Darshan
Gadginmath
Kei
Suzuki
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Awards
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AWARD MERL intern and Researchers wins 2025 IEEE CCTA Best Student Paper Award Date: August 27, 2025
Awarded to: Yingjie Hu (Student, Intern), Karl Berntorp, Stefano Di Cairano (MERL Researchers)
MERL Contact: Stefano Di Cairano
Research Areas: Control, Dynamical Systems, Signal ProcessingBrief- MERL intern Yingjie Hu was recognized as the winner of the 2025 IEEE CCTA Best Student Paper Award for the paper "Optimal Measurement Projection in GNSS-RTK Factor Graph Optimization" written in collaboration with MERL Researchers Karl Berntorp and Stefano Di Cairano during the internship at MERL
The paper develops methods for measurement projections for reducing the computational burden of factor graph optimization algorithms in GNSS applications, thus enabling their use in real-time in a wider range of positioning applications.
The IEEE Conference on Control Technology and Application is the conference of the IEEE Control Systems Society focused on applications and technological advances of control systems
- MERL intern Yingjie Hu was recognized as the winner of the 2025 IEEE CCTA Best Student Paper Award for the paper "Optimal Measurement Projection in GNSS-RTK Factor Graph Optimization" written in collaboration with MERL Researchers Karl Berntorp and Stefano Di Cairano during the internship at MERL
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AWARD MERL work receives IEEE Transactions on Automation Science and Engineering Best New Application Paper Award from IEEE Robotics and Automation Society Date: May 19, 2025
Awarded to: Yehan Ma, Yebin Wang, Stefano Di Cairano, Toshiaki Koike-Akino, Jianlin Guo, Philip Orlik, Xinping Guan and Chenyang Lu
MERL Contacts: Stefano Di Cairano; Jianlin Guo; Toshiaki Koike-Akino; Philip V. Orlik; Yebin Wang
Research Areas: Communications, Control, Machine LearningBrief- The paper “Smart Actuation for End-Edge Industrial Control Systems”, co-authored by MERL intern Yehan Ma, MERL researchers Yebin Wang, Stefano Di Cairano, Toshiaki Koike-Akino, Jianlin Guo, and Philip Orlik, and academic collaborators Xinping Guan and Chenyang Lu, was recognized as the Best New Application Paper of the IEEE Transactions on Automation Science and Engineering (T-ASE), for "a new industrial automation solution that ensures safety operation through coordinated co-design of edge model predictive control and local actuation".
The award recognizes the best application paper published in T-ASE over the previous calendar year, for the significance of new applications, technical merit, originality, potential impact on the field, and clarity of presentation.
- The paper “Smart Actuation for End-Edge Industrial Control Systems”, co-authored by MERL intern Yehan Ma, MERL researchers Yebin Wang, Stefano Di Cairano, Toshiaki Koike-Akino, Jianlin Guo, and Philip Orlik, and academic collaborators Xinping Guan and Chenyang Lu, was recognized as the Best New Application Paper of the IEEE Transactions on Automation Science and Engineering (T-ASE), for "a new industrial automation solution that ensures safety operation through coordinated co-design of edge model predictive control and local actuation".
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AWARD Arvind Raghunathan receives Roberto Tempo Best CDC Paper Award at 2022 IEEE Conference on Decision & Control (CDC) Date: December 8, 2022
Awarded to: Arvind Raghunathan
MERL Contact: Arvind Raghunathan
Research Areas: Control, OptimizationBrief- Arvind Raghunathan, Senior Principal Research Scientist in the Data Analytics group, received the IEEE Control Systems Society Roberto Tempo Best CDC Paper Award. The award was presented at the 2022 IEEE Conference on Decision & Control (CDC).
The award is given annually in honor of Roberto Tempo, the 44th President of the IEEE Control Systems Society (CSS). The Tempo Award Committee selects the best paper from the previous year's CDC based on originality, potential impact on any aspect of control theory, technology, or implementation, and for the clarity of writing. This year's award committee was headed by Prof. Patrizio Colaneri, Politecnico di Milano. Arvind's paper was nominated for the award by Prof. Lorenz Biegler, Carnegie Mellon University, with supporting letters from Prof. Andreas Waechter, Northwestern University, and Prof. Victor Zavala, University of Wisconsin-Madison.
- Arvind Raghunathan, Senior Principal Research Scientist in the Data Analytics group, received the IEEE Control Systems Society Roberto Tempo Best CDC Paper Award. The award was presented at the 2022 IEEE Conference on Decision & Control (CDC).
See All Awards for MERL -
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News & Events
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NEWS MERL researchers present 8 papers at ACC 2026 Date: May 26, 2026 - May 29, 2026
Where: New Orleans, USA
MERL Contacts: Scott A. Bortoff; Vedang M. Deshpande; Stefano Di Cairano; Christopher R. Laughman; Jordan Leung; Hongtao Qiao; Zhaolin Ren; Abraham P. Vinod; Yebin Wang
Research Areas: Control, Dynamical Systems, Optimization, RoboticsBrief- MERL researchers presented 8 papers at the recently concluded American Control Conference (ACC) 2026 in New Orleans, USA. The papers covered a wide range of topics including robust controllable set computation, vapor compression cycle calibration, task-reasoning LLM agents, Minkowski-cost stable MPC, polynomial chaos approximation, invariant-set motion planning, heat-pump MPC architectures, and relaxed barrier-function MPC. Additionally, Zhaolin Ren was an invited speaker at Multi-Agent Dynamic Games workshop, and Abraham Vinod served as a panelist at the Professional Development and Career Advice for Young Professionals session.
As a sponsor of the conference, MERL maintained a booth for open discussions with researchers and students, and hosted a special session to discuss highlights of MERL research and work philosophy.
- MERL researchers presented 8 papers at the recently concluded American Control Conference (ACC) 2026 in New Orleans, USA. The papers covered a wide range of topics including robust controllable set computation, vapor compression cycle calibration, task-reasoning LLM agents, Minkowski-cost stable MPC, polynomial chaos approximation, invariant-set motion planning, heat-pump MPC architectures, and relaxed barrier-function MPC. Additionally, Zhaolin Ren was an invited speaker at Multi-Agent Dynamic Games workshop, and Abraham Vinod served as a panelist at the Professional Development and Career Advice for Young Professionals session.
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NEWS MERL Presents Set-Based Reachability Research for Spacecraft Guidance at NASA Johnson Space Center Date: April 15, 2026 - April 16, 2026
Where: NASA Johnson Space Center, Houston
MERL Contacts: Abraham P. Vinod; Avishai Weiss
Research Areas: Control, Dynamical Systems, Optimization, RoboticsBrief- MERL researchers Avishai Weiss and Abraham Vinod visited NASA Johnson Space Center to present recent advances in set-based reachability analysis for spacecraft guidance, navigation, and control, with an emphasis on powered descent guidance for lunar landing. They delivered an invited talk titled “Safe and Optimal Control for Spacecraft GN&C using Set-Based Reachability Analysis.”
The presentation introduced MERL’s recently developed set-based computational techniques for safe, optimal, and robust spacecraft control, including methods that specialize the approach for computing maximum divert envelopes and enabling real-time landing footprint prediction for landers. The talk was attended by researchers from NASA and the University of Washington, and generated extensive technical discussion.
- MERL researchers Avishai Weiss and Abraham Vinod visited NASA Johnson Space Center to present recent advances in set-based reachability analysis for spacecraft guidance, navigation, and control, with an emphasis on powered descent guidance for lunar landing. They delivered an invited talk titled “Safe and Optimal Control for Spacecraft GN&C using Set-Based Reachability Analysis.”
See All News & Events for Control -
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Internships
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MS0098: Internship - Control and Estimation for Large-Scale Thermofluid Systems
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CA0283: Internship - Active SLAM for Aerial Robots
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MS0260: Internship - Experimental Thermofluid Systems
See All Internships for Control -
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Openings
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MS0268: Research Scientist - Multiphysical Systems
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SA0297: Postdoctoral Research Fellow - AI for Science
See All Openings at MERL -
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Recent Publications
- , "Data-driven Spatial Classification using Multi-Arm Bandits for Monitoring with Energy-Constrained Mobile Robots", IEEE Transactions on Control Systems Technology, June 2026.BibTeX TR2026-078 PDF Video
- @article{Lin2026jun,
- author = {Lin, Xiaoshan and Nayak, Siddharth and {Di Cairano}, Stefano and Vinod, Abraham P.},
- title = {{Data-driven Spatial Classification using Multi-Arm Bandits for Monitoring with Energy-Constrained Mobile Robots}},
- journal = {IEEE Transactions on Control Systems Technology},
- year = 2026,
- month = jun,
- url = {https://www.merl.com/publications/TR2026-078}
- }
- , "GPU-Accelerated Continuous-Time Successive Convexification for Contact-Implicit Legged Locomotion", IEEE International Conference on Robotics and Automation (ICRA), June 2026.BibTeX TR2026-068 PDF
- @inproceedings{Buckner2026jun,
- author = {Buckner, Samuel and Elango, Purnanand},
- title = {{GPU-Accelerated Continuous-Time Successive Convexification for Contact-Implicit Legged Locomotion}},
- booktitle = {IEEE International Conference on Robotics and Automation (ICRA)},
- year = 2026,
- month = jun,
- url = {https://www.merl.com/publications/TR2026-068}
- }
- , "Safe Whole-Body Loco-Manipulation via Combined Model and Learning-based Control", IEEE International Conference on Robotics and Automation (ICRA), June 2026.BibTeX TR2026-072 PDF Video
- @inproceedings{Schperberg2026jun,
- author = {Schperberg, Alexander and Wang, Yeping and {Di Cairano}, Stefano},
- title = {{Safe Whole-Body Loco-Manipulation via Combined Model and Learning-based Control}},
- booktitle = {IEEE International Conference on Robotics and Automation (ICRA)},
- year = 2026,
- month = jun,
- url = {https://www.merl.com/publications/TR2026-072}
- }
- , "LIDIA: Localizing In the Dark with Illumination-Awareness toward Perception-Aware Planning", IEEE International Conference on Robotics and Automation (ICRA), June 2026.BibTeX TR2026-071 PDF
- @inproceedings{Velentzas2026jun,
- author = {{Velentzas, I.G. and Tomita, K.}},
- title = {{LIDIA: Localizing In the Dark with Illumination-Awareness toward Perception-Aware Planning}},
- booktitle = {IEEE International Conference on Robotics and Automation (ICRA)},
- year = 2026,
- month = jun,
- url = {https://www.merl.com/publications/TR2026-071}
- }
- , "Invariant-set motion-planner for unicycle dynamics under closed-loop feedback linearization", American Control Conference (ACC), May 2026.BibTeX TR2026-064 PDF
- @inproceedings{Leung2026may2,
- author = {Leung, Jordan and {Di Cairano}, Stefano},
- title = {{Invariant-set motion-planner for unicycle dynamics under closed-loop feedback linearization}},
- booktitle = {American Control Conference (ACC)},
- year = 2026,
- month = may,
- url = {https://www.merl.com/publications/TR2026-064}
- }
- , "A Comparison of MPC Architectures for a Heat Pump", American Control Conference (ACC), May 2026.BibTeX TR2026-060 PDF
- @inproceedings{Bortoff2026may,
- author = {Bortoff, Scott A. and Quah, Titus and Rawlings, James B.},
- title = {{A Comparison of MPC Architectures for a Heat Pump}},
- booktitle = {American Control Conference (ACC)},
- year = 2026,
- month = may,
- url = {https://www.merl.com/publications/TR2026-060}
- }
- , "A set-based approach for stable MPC with Minkowski cost functions", American Control Conference (ACC), May 2026.BibTeX TR2026-062 PDF
- @inproceedings{Leung2026may,
- author = {Leung, Jordan and Vinod, Abraham P.},
- title = {{A set-based approach for stable MPC with Minkowski cost functions}},
- booktitle = {American Control Conference (ACC)},
- year = 2026,
- month = may,
- url = {https://www.merl.com/publications/TR2026-062}
- }
- , "Robust Controllable Set Computation using Constrained Convex Generators", American Control Conference (ACC), May 2026.BibTeX TR2026-063 PDF
- @inproceedings{Silvestre2026may,
- author = {Silvestre, Daniel and Vinod, Abraham P.},
- title = {{Robust Controllable Set Computation using Constrained Convex Generators}},
- booktitle = {American Control Conference (ACC)},
- year = 2026,
- month = may,
- url = {https://www.merl.com/publications/TR2026-063}
- }
- , "Data-driven Spatial Classification using Multi-Arm Bandits for Monitoring with Energy-Constrained Mobile Robots", IEEE Transactions on Control Systems Technology, June 2026.
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Videos
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