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
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Researchers
Stefano
Di Cairano
Yebin
Wang
Karl
Berntorp
Scott
Bortoff
Mouhacine
Benosman
Claus
Danielson
Avishai
Weiss
Uroš
Kalabić
Rien
Quirynen
Christopher
Laughman
Daniel
Nikovski
Ankush
Chakrabarty
Abraham
Goldsmith
Devesh
Jha
Arvind
Raghunathan
Philip
Orlik
Lei
Zhou
Matthew
Brand
Jianlin
Guo
Saleh
Nabi
Hongtao
Qiao
Koon Hoo
Teo
Toshiaki
Koike-Akino
Diego
Romeres
William
Yerazunis
Alan
Sullivan
Jinyun
Zhang
Petros
Boufounos
Emil
Laftchiev
Chungwei
Lin
Hongbo
Sun
Naohiro
Hayashi
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Awards
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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 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 Dr. Benosman joins the editorial board of the IEEE Control Systems Letters (L-CSS). Date: February 10, 2020
MERL Contact: Mouhacine Benosman
Research Areas: Control, Data Analytics, Dynamical SystemsBrief- Dr. Benosman has been nominated as an associate editor at the IEEE Control Systems Letters (L-CSS).
The L-CSS publishes peer-reviewed brief articles that provide a rapid and concise account of innovative ideas regarding the theory, design, and applications of all aspects of control engineering.
- Dr. Benosman has been nominated as an associate editor at the IEEE Control Systems Letters (L-CSS).
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NEWS Stefano Di Cairano Appointed Inaugural Chair of IEEE CSS Technology Conference Editorial Board Date: December 12, 2019
MERL Contact: Stefano Di Cairano
Research Areas: Control, Dynamical Systems, RoboticsBrief- Stefano Di Cairano has been appointed inaugural chair of the IEEE CSS Technology Conference Editorial Board. In this role Stefano will coordinate the creation and maintenance of the Editorial Board, and will coordinate the editorial board activities supporting the IEEE CCTA conference series, including manuscript assignment to associate editors, monitoring of the manuscript assessment, and program finalization with the conference program chairs. Stefano will also work with the other IEEE CSS Editorial Board Chairs and IEEE CSS Leadership to ensure the quality and improve the processes of IEEE CSS publications.
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Internships
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CD1434: Thermofluidic data-driven modeling
The CD group at MERL is seeking a highly motivated, qualified individual to join our internship program in the summer of 2020. The ideal candidate will be a senior Ph.D. student specializing in fluid mechanics, control, turbulence modeling, reduced-order modeling, and non-convex optimization. Research experience in computational fluid dynamics (CFD), Lagrangian coherent structures, continuous and discreet adjoint methods is very desirable. Familiarity with computational programming languages like MATLAB, Fortran or C++ (openFOAM level) is expected. Publication of results obtained during the internship is expected. The starting date is flexible between April-June 2020, and the internship will last 3-4 months.
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CD1377: Adaptive Optimal Control of Electrical Machines
MERL is seeking a motivated and qualified individual to conduct research in control of electrical machines. The ideal candidate should have solid backgrounds in adaptive dynamic programming and state/parameter estimation for electrical machines, demonstrated capability to publish results in leading conferences/journals, and experience with real-time control experiments involving high power devices. Senior Ph.D. students are encouraged to apply. Start date for this internship is flexible and the duration is about 3 months.
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CD1401: Formal Synthesis for Planning and Control for Autonomous Systems
The Control and Dynamical Systems (CD) group at MERL is seeking a highly motivated intern to conduct research on planning and control by formal methods, in particular temporal logics specifications and their synthesis by mixed-integer inequalities. The ideal candidate is enrolled in a PhD program in Electrical, Mechanical, Aerospace Engineering, Computer Science or related program, with focus on Control Theory. The ideal candidate will have experience in (one or more of) formal methods, particularly temporal logics and signal temporal logics, reachability analysis, abstractions of dynamical systems, hybrid predictive control, and mixed integer programming. Good programming skills in Matlab (or alternatively Python) are required, working knowledge of C/C++ is a plus. The expected duration of the internship is 3-6 months with flexible start date after April 1st, 2020.
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Openings
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Recent Publications
- , "Control Allocation and Quantization of a GEO Satellite with 4DOF Gimbaled Thruster Booms", AAS/AIAA Space Flight Mechanics Meeting, DOI: 10.2514/6.2020-1687, January 2020.BibTeX Download PDFAbout TR2020-008
- @inproceedings{Caverly2020jan,
- author = {Caverly, Ryan and Di Cairano, Stefano and Weiss, Avishai},
- title = {Control Allocation and Quantization of a GEO Satellite with 4DOF Gimbaled Thruster Booms},
- booktitle = {AAS/AIAA Space Flight Mechanics Meeting},
- year = 2020,
- month = jan,
- doi = {10.2514/6.2020-1687},
- url = {https://www.merl.com/publications/TR2020-008}
- }
- , "Control Strategy for Long-Term Station-Keeping on Near-Rectilinear Halo Orbits", AAS/AIAA Space Flight Mechanics Meeting, DOI: 10.2514/6.2020-1459, January 2020.BibTeX Download PDFAbout TR2020-006
- @inproceedings{Muralidharan2020jan,
- author = {Muralidharan, Vivek and Weiss, Avishai and Kalabic, Uros},
- title = {Control Strategy for Long-Term Station-Keeping on Near-Rectilinear Halo Orbits},
- booktitle = {AAS/AIAA Space Flight Mechanics Meeting},
- year = 2020,
- month = jan,
- doi = {10.2514/6.2020-1459},
- url = {https://www.merl.com/publications/TR2020-006}
- }
- , "Trajectory Tracking for Autonomous Vehicles on Varying Road Surfaces by Friction-Adaptive Nonlinear Model Predictive Control", Journal of Vehicle Systems Dynamics, January 2020.BibTeX Download PDFAbout TR2020-005
- @article{Berntorp2020jan,
- author = {Berntorp, Karl and Quirynen, Rien and Uno, Tomoki and Di Cairano, Stefano},
- title = {Trajectory Tracking for Autonomous Vehicles on Varying Road Surfaces by Friction-Adaptive Nonlinear Model Predictive Control},
- journal = {Journal of Vehicle Systems Dynamics},
- year = 2020,
- month = jan,
- url = {https://www.merl.com/publications/TR2020-005}
- }
- , "Efficient Holistic Control: Self-Awareness across Controllers and Wireless Networks", ACM Transactions on Cyber-Physical Systems, January 2020.BibTeX Download PDFAbout TR2020-002
- @article{Ma2020jan,
- author = {Ma, Yehan and Lu, Chenyang and Wang, Yebin},
- title = {Efficient Holistic Control: Self-Awareness across Controllers and Wireless Networks},
- journal = {ACM Transactions on Cyber-Physical Systems},
- year = 2020,
- month = jan,
- url = {https://www.merl.com/publications/TR2020-002}
- }
- , "Finite-Time Convergence of Continuous-Time Optimization Algorithms via Differential Inclusions", Advances in Neural Information Processing Systems (NIPS)- Workshop, January 2020.
- , "Machine Learning Methods for Predicting the Field Compressive Strength of Concrete", Construction And Building Materials, DOI: 10.1016/j.conbuildmat.2019.08.042, Vol. 228, December 2019.BibTeX Download PDFAbout TR2019-096
- @article{DeRousseau2019dec,
- author = {DeRousseau, Mikaela, A. and Laftchiev, Emil and Kasprzyk, Joseph, R. and Balaji, Rajagopalan and Srubar III, Wil V.},
- title = {Machine Learning Methods for Predicting the Field Compressive Strength of Concrete},
- journal = {Construction And Building Materials},
- year = 2019,
- volume = 228,
- month = dec,
- doi = {10.1016/j.conbuildmat.2019.08.042},
- url = {https://www.merl.com/publications/TR2019-096}
- }
- , "Robust Optimization for Trajectory-Centric Model-based Reinforcement Learning", NeurIPS Workshop on Safety and Robustness in Decision Making, December 2019.BibTeX Download PDFAbout TR2019-156
- @inproceedings{Jha2019dec2,
- author = {Jha, Devesh and Kolaric, Patrik and Romeres, Diego and Raghunathan, Arvind and Benosman, Mouhacine and Nikovski, Daniel N.},
- title = {Robust Optimization for Trajectory-Centric Model-based Reinforcement Learning},
- booktitle = {NeurIPS Workshop on Safety and Robustness in Decision Making},
- year = 2019,
- month = dec,
- url = {https://www.merl.com/publications/TR2019-156}
- }
- , "Robust Nonlinear State Estimation for Thermal-Fluid Models Using Reduced-Order Models: The Case of the Boussinesq Equations", IEEE Conference on Decision and Control (CDC), December 2019.BibTeX Download PDFAbout TR2019-147
- @inproceedings{Benosman2019dec,
- author = {Benosman, Mouhacine and Borggaard, Jeff},
- title = {Robust Nonlinear State Estimation for Thermal-Fluid Models Using Reduced-Order Models: The Case of the Boussinesq Equations},
- booktitle = {IEEE Conference on Decision and Control (CDC)},
- year = 2019,
- month = dec,
- url = {https://www.merl.com/publications/TR2019-147}
- }
- , "Control Allocation and Quantization of a GEO Satellite with 4DOF Gimbaled Thruster Booms", AAS/AIAA Space Flight Mechanics Meeting, DOI: 10.2514/6.2020-1687, January 2020.
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Videos
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MERL Research on Autonomous Vehicles
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MPC control and particle filter-based planning demonstration using mini-cars
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Fly Cut
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Particle filter-based planning demonstration using mini-cars
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MPC for Laser Cutting
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Car Path Planning
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MPC for Satellites
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HVAC Lab & Controls
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Experimental Validation of Reachability-based Decision Making for Autonomous Driving
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Free Downloads
