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
Karl
Berntorp
Scott A.
Bortoff
Mouhacine
Benosman
Avishai
Weiss
Ankush
Chakrabarty
Christopher R.
Laughman
Daniel N.
Nikovski
Diego
Romeres
Devesh K.
Jha
Philip V.
Orlik
Arvind
Raghunathan
Abraham P.
Vinod
Abraham
Goldsmith
Jianlin
Guo
William S.
Yerazunis
Vedang M.
Deshpande
Toshiaki
Koike-Akino
Chungwei
Lin
Hongtao
Qiao
Matthew
Brand
Koon Hoo
Teo
Yanting
Ma
Hassan
Mansour
Pedro
Miraldo
Jinyun
Zhang
Petros T.
Boufounos
Siddarth
Jain
Kieran
Parsons
Hongbo
Sun
Gordon
Wichern
James
Queeney
Luigi
Vanfretti
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Awards
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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).
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AWARD Best Student Paper Award at the IEEE Conference on Control Technology and Applications Date: August 26, 2020
Awarded to: Marcus Greiff, Anders Robertsson, Karl Berntorp
MERL Contact: Karl Berntorp
Research Areas: Control, Signal ProcessingBrief- Marcus Greiff, a former MERL intern from the Department of Automatic Control, Lund University, Sweden, won one of three 2020 CCTA Outstanding Student Paper Awards and the Best Student Paper Award at the 2020 IEEE Conference on Control Technology and Applications. The research leading up to the awarded paper titled 'MSE-Optimal Measurement Dimension Reduction in Gaussian Filtering', concerned how to select a reduced set of measurements in estimation applications while minimally degrading performance, was done in collaboration with Karl Berntorp at MERL.
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AWARD MERL Researcher Devesh Jha Wins the Rudolf Kalman Best Paper Award 2019 Date: October 10, 2019
Awarded to: Devesh Jha, Nurali Virani, Zhenyuan Yuan, Ishana Shekhawat and Asok Ray
MERL Contact: Devesh K. Jha
Research Areas: Artificial Intelligence, Control, Data Analytics, Machine Learning, RoboticsBrief- MERL researcher Devesh Jha has won the Rudolf Kalman Best Paper Award 2019 for the paper entitled "Imitation of Demonstrations Using Bayesian Filtering With Nonparametric Data-Driven Models". This paper, published in a Special Commemorative Issue for Rudolf E. Kalman in the ASME JDSMC in March 2018, uses Bayesian filtering for imitation learning in Hidden Mode Hybrid Systems. This award is given annually by the Dynamic Systems and Control Division of ASME to the authors of the best paper published in the ASME Journal of Dynamic Systems Measurement and Control during the preceding year.
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News & Events
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NEWS Karl Berntorp joins the Editorial Board of IEEE Transactions on Control Systems Technology Date: December 7, 2023
MERL Contact: Karl Berntorp
Research Areas: Control, Dynamical SystemsBrief- Karl Berntorp has joined the Editorial Board of the IEEE Transactions on Control Systems Technology (T-CST) as an Associate Editor. The IEEE T-CST publishes peer-reviewed papers on technological advances in the design, realization, and operation of control systems, and bridges the gap between the theory and practice of control engineering.
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NEWS Ankush Chakrabarty served as Co-Chair of ACM BALANCES 2023 Date: November 14, 2023
Where: Istanbul, Turkey
MERL Contact: Ankush Chakrabarty
Research Areas: Control, Data Analytics, Machine Learning, Multi-Physical Modeling, OptimizationBrief- Ankush Chakrabarty, Principal Research Scientist in the Multiphysical Systems team at MERL, served as Co-Chair at the 3rd ACM International Workshop on Big Data and Machine Learning for Smart Buildings and Cities (BALANCES'23). The workshop places spotlights on two different IEA EBC Annexes: the Annex 81 - Data-Driven Smart Buildings and Annex 82 - Energy Flexible Buildings Towards Resilient Low Carbon Energy Systems.
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Internships
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CA1940: Autonomous vehicle planning and contro in uncertain environments
MERL is seeking a highly motivated and qualified intern to collaborate with the Control for Autonomy team in research on planning and control for autonomous vehicles in uncertain surrounding environments. The research domain includes algorithms for path planning and control in environments that are uncertain and perceived by sensing and predicted according to models and data. The ideal candidate is expected to be working towards a PhD with strong emphasis in vehicle guidance and control, and to have interest and background in as many as possible of: vehicle dynamics modeling and control, sensor uncertainty modeling, data-driven prediction, predictive control for uncertain systems, motion planning. Good programming skills in MATLAB, Python are required, knowledge of C/C++, rapid prototyping systems, automatic code generation, vehicle simulation packages (CarSim, CarMaker) or ROS are a plus. The expected start of of the internship is in the late Spring/Early Summer 2022, for a duration of 3-6 months.
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CA2131: Collaborative Legged Robots
MERL is seeking a highly motivated and qualified intern to collaborate with the Control for Autonomy team in research on control and planning algorithms for legged robots for support activities of and collaboration with humans. The ideal candidate is expected to be working towards a PhD with strong emphasis in robotics control and planning and to have interest and background in as many as possible of: motion planning algorithms, control for legged robot locomotions, legged robots, perception and sensing with multiple sensors, SLAM, vision-based control. Good programming skills in Python or C/C++ are required. The expected start of of the internship is flexible, with duration of 3--6 months.
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CA2132: Optimization Algorithms for Motion Planning and Predictive Control
MERL is looking for a highly motivated and qualified individual to work on tailored computational algorithms for optimization-based motion planning and predictive control applications in autonomous systems (vehicles, mobile robots). The ideal candidate should have experience in either one or multiple of the following topics: convex and non-convex optimization, stochastic predictive control (e.g., scenario trees), interaction-aware motion planning, machine learning, learning-based model predictive control, mathematical programs with complementarity constraints (MPCCs), optimal control, and real-time optimization. PhD students in engineering or mathematics, especially with a focus on research related to any of the above topics are encouraged to apply. Publication of relevant results in conference proceedings or journals is expected. Capability of implementing the designs and algorithms in MATLAB/Python is required; coding parts of the algorithms in C/C++ is a plus. The expected duration of the internship is 3 months, and the start date is flexible.
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Openings
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Recent Publications
- "Control Challenges and Opportunities in Building Automation" in The Impact of Automatic Control Research on Industrial Innovation: Enabling a Sustainable Future, February 2024.BibTeX TR2024-011 PDF
- @incollection{Bortoff2024feb,
- author = {Bortoff, Scott A. and Eisenhower, Bryan and Adetola, Veronica and O'Neil, Zheng},
- title = {Control Challenges and Opportunities in Building Automation},
- booktitle = {The Impact of Automatic Control Research on Industrial Innovation: Enabling a Sustainable Future},
- year = 2024,
- month = feb,
- url = {https://www.merl.com/publications/TR2024-011}
- }
, - "Lunar Landing with Feasible Divert using Controllable Sets", AIAA SciTech, DOI: 10.2514/6.2024-0324, January 2024, pp. AIAA 2024-0324.BibTeX TR2024-004 PDF
- @inproceedings{Srinivas2024jan,
- author = {Srinivas, Neeraj and Vinod, Abraham P. and Di Cairano, Stefano and Weiss, Avishai},
- title = {Lunar Landing with Feasible Divert using Controllable Sets},
- booktitle = {AIAA SCITECH 2024 Forum},
- year = 2024,
- pages = {AIAA 2024--0324},
- month = jan,
- doi = {10.2514/6.2024-0324},
- url = {https://www.merl.com/publications/TR2024-004}
- }
, - "Perception-Aware Model Predictive Control for Constrained Control in Unknown Environments", Automatica, DOI: 10.1016/j.automatica.2023.111418, December 2023.BibTeX TR2023-147 PDF
- @article{Bonzanini2023dec,
- author = {Bonzanini, Angelo Domenico and Mesbah, Ali and Di Cairano, Stefano},
- title = {Perception-Aware Model Predictive Control for Constrained Control in Unknown Environments},
- journal = {Automatica},
- year = 2023,
- month = dec,
- doi = {10.1016/j.automatica.2023.111418},
- url = {https://www.merl.com/publications/TR2023-147}
- }
, - "Preference-Guided Bayesian Optimization for Control Policy Learning: Application to Personalized Plasma Medicine", Advances in Neural Information Processing Systems (NeurIPS), December 2023.BibTeX TR2023-146 PDF
- @inproceedings{Shao2023dec,
- author = {Shao, Ketong and Romeres, Diego and Chakrabarty, Ankush and Mesbah, Ali},
- title = {Preference-Guided Bayesian Optimization for Control Policy Learning: Application to Personalized Plasma Medicine},
- booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
- year = 2023,
- month = dec,
- url = {https://www.merl.com/publications/TR2023-146}
- }
, - "Physics-Constrained Deep Autoencoded Kalman Filters for Estimating Vapor Compression System States", IEEE Control Systems Letters, DOI: 10.1109/LCSYS.2023.3334959, November 2023.BibTeX TR2023-138 PDF
- @article{Deshpande2023nov,
- author = {Deshpande, Vedang M. and Chakrabarty, Ankush and Vinod, Abraham P. and Laughman, Christopher R.},
- title = {Physics-Constrained Deep Autoencoded Kalman Filters for Estimating Vapor Compression System States},
- journal = {IEEE Control Systems Letters},
- year = 2023,
- month = nov,
- doi = {10.1109/LCSYS.2023.3334959},
- url = {https://www.merl.com/publications/TR2023-138}
- }
, - "Scalable Optimal Power Management for Large-Scale Battery Energy Storage Systems", IEEE Transactions on Transportation Electrification, DOI: 10.1109/TTE.2023.3331243, November 2023.BibTeX TR2023-137 PDF
- @article{Farakhor2023nov,
- author = {Farakhor, Amir and Wu, Di and Wang, Yebin and Fang, Huazhen},
- title = {Scalable Optimal Power Management for Large-Scale Battery Energy Storage Systems},
- journal = {IEEE Transactions on Transportation Electrification},
- year = 2023,
- month = nov,
- doi = {10.1109/TTE.2023.3331243},
- issn = {2332-7782},
- url = {https://www.merl.com/publications/TR2023-137}
- }
, - "A System-Level Cooperative Multi-Agent GNSS Positioning Solution", IEEE Transactions on Control Systems Technology, DOI: 10.1109/TCST.2023.3307339, Vol. 32, No. 1, pp. 158-173, October 2023.BibTeX TR2023-135 PDF
- @article{Greiff2023oct,
- author = {Greiff, Marcus and Di Cairano, Stefano and Kim, Kyeong Jin and Berntorp, Karl},
- title = {A System-Level Cooperative Multi-Agent GNSS Positioning Solution},
- journal = {IEEE Transactions on Control Systems Technology},
- year = 2023,
- volume = 32,
- number = 1,
- pages = {158--173},
- month = oct,
- doi = {10.1109/TCST.2023.3307339},
- url = {https://www.merl.com/publications/TR2023-135}
- }
, - "High-Fidelity Simulation of Horizon-Based Optical Navigation with Open-Source Software", International Astronautical Congress (IAC), October 2023, pp. IAC-23,C1,5,9,x78805.BibTeX TR2023-128 PDF
- @inproceedings{Shimane2023oct,
- author = {Shimane, Yuri and Miraldo, Pedro and Berntorp, Karl and Greiff, Marcus and Elango, Purnanand and Weiss, Avishai},
- title = {High-Fidelity Simulation of Horizon-Based Optical Navigation with Open-Source Software},
- booktitle = {International Astronautical Congress (IAC)},
- year = 2023,
- pages = {IAC--23,C1,5,9,x78805},
- month = oct,
- url = {https://www.merl.com/publications/TR2023-128}
- }
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- "Control Challenges and Opportunities in Building Automation" in The Impact of Automatic Control Research on Industrial Innovation: Enabling a Sustainable Future, February 2024.
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