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.
Quick Links
-
Researchers
Stefano
Di Cairano
Yebin
Wang
Avishai
Weiss
Scott A.
Bortoff
Ankush
Chakrabarty
Christopher R.
Laughman
Abraham P.
Vinod
Daniel N.
Nikovski
Diego
Romeres
Devesh K.
Jha
Arvind
Raghunathan
Abraham
Goldsmith
Philip V.
Orlik
William S.
Yerazunis
Vedang M.
Deshpande
Hongtao
Qiao
Jianlin
Guo
Chungwei
Lin
Purnanand
Elango
Toshiaki
Koike-Akino
Matthew
Brand
Dehong
Liu
Yanting
Ma
Pedro
Miraldo
Alexander
Schperberg
Bingnan
Wang
Petros T.
Boufounos
Hassan
Mansour
Ye
Wang
Gordon
Wichern
Jinyun
Zhang
Siddarth
Jain
Saviz
Mowlavi
Kieran
Parsons
Hongbo
Sun
Kei
Suzuki
-
Awards
-
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
-
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".
-
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 Control -
-
News & Events
-
NEWS Diego Romeres Delivers Invited Talks at Fraunhofer Italia and the University of Padua Date: July 16, 2025 - July 18, 2025
MERL Contact: Diego Romeres
Research Areas: Artificial Intelligence, Control, Machine Learning, Optimization, Robotics, Human-Computer InteractionBrief- MERL researcher Diego Romeres was invited to present MERL's latest research at two institutions in Italy this July, focusing on human-robot collaboration and LLM-driven assembly systems.
On July 16th, Dr. Romeres delivered a talk titled “Human-Robot Collaborative Assembly” at Fraunhofer Italia – Innovation Engineering Center (EIC) in Bolzano. His presentation showcased research on human-robot collaboration for efficient and flexible assembly processes. Fraunhofer Italia EIC is a non-profit research institute focused on enabling digital and sustainable transformation through applied innovation in close collaboration with both public and private sectors.
Two days later, on July 18th, Dr. Romeres was hosted by the University of Padua, one of Europe’s oldest and most renowned universities. His invited lecture, “Robot Assembly through Human Collaboration & Large Language Models”, explored how artificial intelligence can enhance human-robot synergy in complex assembly tasks.
- MERL researcher Diego Romeres was invited to present MERL's latest research at two institutions in Italy this July, focusing on human-robot collaboration and LLM-driven assembly systems.
-
NEWS MERL researchers present 13 papers at ACC 2025 Date: July 8, 2025 - July 10, 2025
Where: Denver, USA
MERL Contacts: Ankush Chakrabarty; Vedang M. Deshpande; Stefano Di Cairano; Purnanand Elango; Jordan Leung; Saviz Mowlavi; Diego Romeres; Abraham P. Vinod; Yebin Wang; Avishai Weiss
Research Areas: Control, Dynamical Systems, Electric Systems, Machine Learning, Multi-Physical Modeling, RoboticsBrief- MERL researchers presented 13 papers at the recently concluded American Control Conference (ACC) 2025 in Denver, USA. The papers covered a wide range of topics including Bayesian optimization for personalized medicine, machine learning for battery performance in eVTOLs, model predictive control for space and building systems, process systems engineering for sustainability, GNSS-RTK optimization, convex set manipulation, PDE control, servo system modeling, battery fault diagnosis, truck fleet coordination, interactive motion planning, and satellite station keeping. Additionally, MERL researchers (Vedang Deshpande and Ankush Chakrabarty) organized an invited session on design and optimization of energy systems.
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 13 papers at the recently concluded American Control Conference (ACC) 2025 in Denver, USA. The papers covered a wide range of topics including Bayesian optimization for personalized medicine, machine learning for battery performance in eVTOLs, model predictive control for space and building systems, process systems engineering for sustainability, GNSS-RTK optimization, convex set manipulation, PDE control, servo system modeling, battery fault diagnosis, truck fleet coordination, interactive motion planning, and satellite station keeping. Additionally, MERL researchers (Vedang Deshpande and Ankush Chakrabarty) organized an invited session on design and optimization of energy systems.
See All News & Events for Control -
-
Internships
-
CA0178: Internship - Planning and Control of Multi-robot systems
MERL is seeking a highly motivated intern to collaborate in the development decision making, planning and control for teams of ground robot in task such as coverage control, monitoring and pursuit-evasion. The ideal candidate is a PhD student with strong experience in planning and control of multi-agent systems, with background in advanced model-based (e.g., MPC) and learning-based (e.g., RL) methods. The results of the internship are expected to be published in top-tier conferences and/or journals. The internship will take place during Fall/Winter 2025 (exact dates are flexible) with an expected duration of 3-6 months.
Please use your cover letter to explain how you meet the following requirements, preferably with links to papers, code repositories, etc., indicating your proficiency.
Required Experience
- Current enrollment in a PhD program in Mechanical, Electrical, Aerospace Engineering, Computer Science or related programs, with a focus on Robotics and/or Control Systems
- Experience in as many as possible of:
- Formal methods and set based methods (temporal logics, reachability, invariance)
- Model predictive control (design, analysis, solvers)
- Reinforcement learning for planning
- Cooperative planning and control for multi-agent systems
- Programming in Python or Matlab or Julia
Additional Useful Experience
- Knowledge of one or more physics simulators for robotics (e.g., MuJoco)
- Experience with coverage control and pursuit-evasion problems
- Programming in C/C++ or Simulink code generation
-
CA0166: Internship - Spacecraft Guidance, Navigation, and Control
MERL is seeking a highly motivated graduate student for a research position in guidance, navigation, and control of spacecraft. The ideal candidate is a PhD student with strong experience in trajectory generation and sequential convex optimization, stochastic optimal control and state estimation, and astrodynamics and the three-body problem. Publication of results produced during the internship is expected. The expected duration of the internship is 3-6 months with a flexible start date.
Required Specific Experience
- Current enrollment in a PhD program in Aerospace, Mechanical, Electrical Engineering, or a related field
- Familiarity with convex optimization solvers
- Strong programming skills in Matlab, Python, and/or C/C++
-
MS0098: Internship - Control and Estimation for Large-Scale Thermofluid Systems
MERL is seeking a motivated graduate student to research methods for state and parameter estimation and optimization of large-scale systems for process applications. Representative applications include large vapor-compression cycles and other multiphysical systems for energy conversion that couple thermodynamic, fluid, and electrical domains. The ideal candidate would have a solid background in control and estimation, numerical methods, and optimization; strong programming skills and experience with Julia/Python/Matlab are also expected. Knowledge of the fundamental physics of thermofluid flows (e.g., thermodynamics, heat transfer, and fluid mechanics), nonlinear dynamics, or equation-oriented languages (Modelica, gPROMS) is a plus. The expected duration of this internship is 3 months.
See All Internships for Control -
-
Openings
See All Openings at MERL -
Recent Publications
- , "Energy-constrained multi-robot exploration for autonomous map building", IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), October 2025.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,
- month = oct,
- url = {https://www.merl.com/publications/TR2025-131}
- }
- , "Offline Imitation Learning upon Arbitrary Demonstrations by Pre-Training Dynamics Representations", IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), October 2025.BibTeX TR2025-147 PDF
- @inproceedings{Ma2025oct,
- author = {Ma, Haitong and Dai, Bo and Ren, Zhaolin and Wang, Yebin and Li, Na},
- title = {{Offline Imitation Learning upon Arbitrary Demonstrations by Pre-Training Dynamics Representations}},
- booktitle = {IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
- year = 2025,
- month = oct,
- url = {https://www.merl.com/publications/TR2025-147}
- }
- , "Energy-Efficient Motion Planner for Legged Robots", IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), October 2025.BibTeX TR2025-151 PDF Video
- @inproceedings{Schperberg2025oct,
- author = {Schperberg, Alexander and Menner, Marcel and {Di Cairano}, Stefano},
- title = {{Energy-Efficient Motion Planner for Legged Robots}},
- booktitle = {IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
- year = 2025,
- month = oct,
- url = {https://www.merl.com/publications/TR2025-151}
- }
- , "AI-Driven Scenario Discovery: Diffusion Models and Multi-Armed Bandits for Building Control Validation", Energy and Buildings, DOI: 10.1016/j.enbuild.2025.116207, September 2025.BibTeX TR2025-132 PDF
- @article{Tang2025sep,
- author = {Tang, Wei-Ting and Vinod, Abraham P. and Germain, François G and Paulson, Joel A. and Laughman, Christopher R. and Chakrabarty, Ankush},
- title = {{AI-Driven Scenario Discovery: Diffusion Models and Multi-Armed Bandits for Building Control Validation}},
- journal = {Energy and Buildings},
- year = 2025,
- month = sep,
- doi = {10.1016/j.enbuild.2025.116207},
- url = {https://www.merl.com/publications/TR2025-132}
- }
- , "A Dynamic Analysis of Refrigerant Mass in Vapor Compression Cycles", International Modelica Conference, September 2025.BibTeX TR2025-135 PDF
- @inproceedings{Bortoff2025sep,
- author = {Bortoff, Scott A. and Deshpande, Vedang M. and Laughman, Christopher R. and Qiao, Hongtao},
- title = {{A Dynamic Analysis of Refrigerant Mass in Vapor Compression Cycles}},
- booktitle = {International Modelica Conference},
- year = 2025,
- month = sep,
- url = {https://www.merl.com/publications/TR2025-135}
- }
- , "Robust Unfalsified Control of a Heat Pump", IEEE Conference on Control Technology and Applications (CCTA), August 2025.BibTeX TR2025-128 PDF
- @inproceedings{Bortoff2025aug,
- author = {Bortoff, Scott A. and Tsuji, Kosei},
- title = {{Robust Unfalsified Control of a Heat Pump}},
- booktitle = {IEEE Conference on Control Technology and Applications (CCTA)},
- year = 2025,
- month = aug,
- url = {https://www.merl.com/publications/TR2025-128}
- }
- , "A Real-time High C-rate Lithium-ion Battery Fast Charging Strategy", IEEE Conference on Control Technology and Applications (CCTA), August 2025.BibTeX TR2025-127 PDF
- @inproceedings{Lu2025aug,
- author = {Lu, Zehui and Tu, Hao and Fang, Huazhen and Wang, Yebin and Mou, Shaoshuai},
- title = {{A Real-time High C-rate Lithium-ion Battery Fast Charging Strategy}},
- booktitle = {IEEE Conference on Control Technology and Applications (CCTA)},
- year = 2025,
- month = aug,
- url = {https://www.merl.com/publications/TR2025-127}
- }
- , "Optimal Measurement Projection in GNSS-RTK Factor Graph Optimization", IEEE Conference on Control Technology and Applications (CCTA), August 2025.BibTeX TR2025-118 PDF
- @inproceedings{Hu2025aug,
- author = {Hu, Yingjie and {Di Cairano}, Stefano and Berntorp, Karl},
- title = {{Optimal Measurement Projection in GNSS-RTK Factor Graph Optimization}},
- booktitle = {IEEE Conference on Control Technology and Applications (CCTA)},
- year = 2025,
- month = aug,
- url = {https://www.merl.com/publications/TR2025-118}
- }
- , "Energy-constrained multi-robot exploration for autonomous map building", IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), October 2025.
-
Videos
-
Software & Data Downloads
