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
Diego
Romeres
Arvind
Raghunathan
Abraham
Goldsmith
Philip V.
Orlik
William S.
Yerazunis
Vedang M.
Deshpande
Chungwei
Lin
Hongtao
Qiao
Jianlin
Guo
Purnanand
Elango
Toshiaki
Koike-Akino
Yanting
Ma
Matthew
Brand
Dehong
Liu
Pedro
Miraldo
Alexander
Schperberg
Bingnan
Wang
Petros T.
Boufounos
Hassan
Mansour
Ye
Wang
Gordon
Wichern
Jinyun
Zhang
Siddarth
Jain
Jordan
Leung
Saviz
Mowlavi
Kieran
Parsons
Zhaolin
Ren
Hongbo
Sun
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 at NeurIPS 2025 presented 2 conference papers, 5 workshop papers, and organized a workshop. Date: December 2, 2025 - December 7, 2025
Where: San Diego
MERL Contacts: Petros T. Boufounos; Anoop Cherian; Radu Corcodel; Stefano Di Cairano; Chiori Hori; Christopher R. Laughman; Suhas Anand Lohit; Pedro Miraldo; Saviz Mowlavi; Kuan-Chuan Peng; Arvind Raghunathan; Diego Romeres; Yuki Shirai; Abraham P. Vinod; Pu (Perry) Wang
Research Areas: Artificial Intelligence, Computational Sensing, Computer Vision, Control, Data Analytics, Dynamical Systems, Machine Learning, Multi-Physical Modeling, Optimization, Robotics, Signal Processing, Speech & AudioBrief- MERL researchers presented 2 main-conference papers and 5 workshop papers, as well as organized a workshop, at NeurIPS 2025.
Main Conference Papers:
1) Sorachi Kato, Ryoma Yataka, Pu Wang, Pedro Miraldo, Takuya Fujihashi, and Petros Boufounos, "RAPTR: Radar-based 3D Pose Estimation using Transformer", Code available at: https://github.com/merlresearch/radar-pose-transformer
2) Runyu Zhang, Arvind Raghunathan, Jeff Shamma, and Na Li, "Constrained Optimization From a Control Perspective via Feedback Linearization"
Workshop Papers:
1) Yuyou Zhang, Radu Corcodel, Chiori Hori, Anoop Cherian, and Ding Zhao, "SpinBench: Perspective and Rotation as a Lens on Spatial Reasoning in VLMs", NeuriIPS 2025 Workshop on SPACE in Vision, Language, and Embodied AI (SpaVLE) (Best Paper Runner-up)
2) Xiaoyu Xie, Saviz Mowlavi, and Mouhacine Benosman, "Smooth and Sparse Latent Dynamics in Operator Learning with Jerk Regularization", Workshop on Machine Learning and the Physical Sciences (ML4PS)
3) Spencer Hutchinson, Abraham Vinod, François Germain, Stefano Di Cairano, Christopher Laughman, and Ankush Chakrabarty, "Quantile-SMPC for Grid-Interactive Buildings with Multivariate Temporal Fusion Transformers", Workshop on UrbanAI: Harnessing Artificial Intelligence for Smart Cities (UrbanAI)
4) Yuki Shirai, Kei Ota, Devesh Jha, and Diego Romeres, "Sim-to-Real Contact-Rich Pivoting via Optimization-Guided RL with Vision and Touch", Worskhop on Embodied World Models for Decision Making
5) Mark Van der Merwe and Devesh Jha, "In-Context Policy Iteration for Dynamic Manipulation", Workshop on Embodied World Models for Decision Making
Workshop Organized:
MERL members co-organized the Multimodal Algorithmic Reasoning (MAR) Workshop (https://marworkshop.github.io/neurips25/). Organizers: Anoop Cherian (Mitsubishi Electric Research Laboratories), Kuan-Chuan Peng (Mitsubishi Electric Research Laboratories), Suhas Lohit (Mitsubishi Electric Research Laboratories), Honglu Zhou (Salesforce AI Research), Kevin Smith (Massachusetts Institute of Technology), and Joshua B. Tenenbaum (Massachusetts Institute of Technology).
- MERL researchers presented 2 main-conference papers and 5 workshop papers, as well as organized a workshop, at NeurIPS 2025.
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NEWS Abraham Vinod Delivers Invited Talks at The University of Texas at Austin and The University of Texas at Dallas Date: November 11, 2025 - November 13, 2025
MERL Contact: Abraham P. Vinod
Research Areas: Artificial Intelligence, Control, Dynamical Systems, Machine Learning, Optimization, RoboticsBrief- MERL researcher Abraham Vinod was invited to present MERL's latest research at the University of Texas at Austin and The University of Texas at Dallas this November. His talk discussed a tractable set-based method for a broad class of robust control problems with nonlinear dynamics and bounded uncertainty, with applications to powered descent guidance and drone motion planning problems. Additionally, he also presented MERL's recent research on environmental monitoring using hetereogenous robots, with applications in disaster management and search-and-rescue.
See All News & Events for Control -
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Internships
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EA0228: Internship - Constraint Modeling and Optimal Control
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CA0274: Internship - Infrastructure inspection/repair using heterogenous robot teams
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CA0250: Internship - Perception and Control for Legged Loco-Manipulation
See All Internships for Control -
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Openings
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CA0093: Research Scientist - Control for Autonomous Systems
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MS0268: Research Scientist - Multiphysical Systems
See All Openings at MERL -
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Recent Publications
- , "Relaxed barrier function based model predictive control with hard input constraints", IEEE Control Systems Letters, December 2025.BibTeX TR2026-005 PDF
- @article{Castroviejo-Fernandez2025dec,
- author = {Castroviejo-Fernandez, Miguel and Leung, Jordan},
- title = {{Relaxed barrier function based model predictive control with hard input constraints}},
- journal = {IEEE Control Systems Letters},
- year = 2025,
- month = dec,
- url = {https://www.merl.com/publications/TR2026-005}
- }
- , "Motion Planning for Information Acquisition via Continuous-time Successive Convexification", IEEE Conference on Decision and Control (CDC), December 2025.BibTeX TR2025-170 PDF
- @inproceedings{Uzun2025dec,
- author = {Uzun, Samet and Acikmese, Behcet and {Di Cairano}, Stefano},
- title = {{Motion Planning for Information Acquisition via Continuous-time Successive Convexification}},
- booktitle = {IEEE Conference on Decision and Control (CDC)},
- year = 2025,
- month = dec,
- url = {https://www.merl.com/publications/TR2025-170}
- }
- , "Set-based lossless convexification for a class of robust nonlinear optimal control problems", IEEE Conference on Decision and Control (CDC), December 2025.BibTeX TR2025-160 PDF
- @inproceedings{Vinod2025dec,
- author = {Vinod, Abraham P. and Kamath, Abhinav and Weiss, Avishai and {Di Cairano}, Stefano},
- title = {{Set-based lossless convexification for a class of robust nonlinear optimal control problems}},
- booktitle = {IEEE Conference on Decision and Control (CDC)},
- year = 2025,
- month = dec,
- url = {https://www.merl.com/publications/TR2025-160}
- }
- , "Quantile-SMPC for Grid-Interactive Buildings with Multivariate Temporal Fusion Transformers", Advances in Neural Information Processing Systems (NeurIPS) Workshop on UrbanAI, December 2025.BibTeX TR2026-001 PDF
- @inproceedings{Hutchinson2025dec,
- author = {{{Hutchinson, Spencer and Vinod, Abraham P. and Germain, François G and Di Cairano, Stefano and Laughman, Christopher R. and Chakrabarty, Ankush}}},
- title = {{{Quantile-SMPC for Grid-Interactive Buildings with Multivariate Temporal Fusion Transformers}}},
- booktitle = {Advances in Neural Information Processing Systems (NeurIPS) Workshop on UrbanAI},
- year = 2025,
- month = dec,
- url = {https://www.merl.com/publications/TR2026-001}
- }
- , "Constrained Optimization From a Control Perspective via Feedback Linearization", The Thirty-Ninth Annual Conference on Neural Information Processing Systems (NuerIPS), December 2025.BibTeX TR2025-165 PDF
- @inproceedings{Zhang2025dec,
- author = {Zhang, Runyu and Raghunathan, Arvind and Shamma, Jeff and Li, Na},
- title = {{Constrained Optimization From a Control Perspective via Feedback Linearization}},
- booktitle = {The Thirty-Ninth Annual Conference on Neural Information Processing Systems (NuerIPS)},
- year = 2025,
- month = dec,
- url = {https://www.merl.com/publications/TR2025-165}
- }
- , "Application of Optimal Control to Time-Resolution Protocol for Quantum Sensing", Physical Review, DOI: 10.1103/1nsd-2574, Vol. 112, pp. 052608, November 2025.BibTeX TR2025-161 PDF
- @article{Lin2025nov,
- author = {Lin, Chungwei and Ding, Qi (Andy) and Ma, Yanting},
- title = {{Application of Optimal Control to Time-Resolution Protocol for Quantum Sensing}},
- journal = {Physical Review},
- year = 2025,
- volume = 112,
- pages = 052608,
- month = nov,
- doi = {10.1103/1nsd-2574},
- url = {https://www.merl.com/publications/TR2025-161}
- }
- , "Optimization-Based Phase-Constrained x-Axis Crossing Control for Station-Keeping on Libration Point Orbits", Journal of the Astronautical Sciences, DOI: 10.1007/s40295-025-00543-1, Vol. 72, No. 6, pp. 59, November 2025.BibTeX TR2026-004 PDF
- @article{Shimane2025dec3,
- author = {Shimane, Yuri and Ho, Koki and Weiss, Avishai},
- title = {{Optimization-Based Phase-Constrained x-Axis Crossing Control for Station-Keeping on Libration Point Orbits}},
- journal = {Journal of the Astronautical Sciences},
- year = 2025,
- volume = 72,
- number = 6,
- pages = 59,
- month = dec,
- doi = {10.1007/s40295-025-00543-1},
- url = {https://www.merl.com/publications/TR2026-004}
- }
- , "Energy-constrained multi-robot exploration for autonomous map building", IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), DOI: 10.1109/IROS60139.2025.11247332, October 2025, pp. 9154-9161.BibTeX TR2025-131 PDF
- @inproceedings{Karumanchi2025oct,
- author = {Karumanchi, Sambhu and Rokaha, Bhagawan and Schperberg, Alexander and Vinod, Abraham P.},
- title = {{Energy-constrained multi-robot exploration for autonomous map building}},
- booktitle = {IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
- year = 2025,
- pages = {9154--9161},
- month = oct,
- doi = {10.1109/IROS60139.2025.11247332},
- url = {https://www.merl.com/publications/TR2025-131}
- }
- , "Relaxed barrier function based model predictive control with hard input constraints", IEEE Control Systems Letters, December 2025.
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