Dynamical Systems
Exploiting nonlinearity and shaping dynamics in creative and deeply mathematical ways.
We apply dynamical systems theory in applications ranging from space probe trajectory optimization to elevator suspensions. We also develop fundamental theory and computational methods in fluid dynamics.
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Researchers
Mouhacine
Benosman
Stefano
Di Cairano
Yebin
Wang
Scott
Bortoff
Karl
Berntorp
Christopher
Laughman
Hongtao
Qiao
Saleh
Nabi
Rien
Quirynen
Avishai
Weiss
Claus
Danielson
Uroš
Kalabić
Daniel
Nikovski
Abraham
Goldsmith
Petros
Boufounos
Devesh
Jha
Hassan
Mansour
Diego
Romeres
Hongbo
Sun
William
Yerazunis
Jinyun
Zhang
Naohiro
Hayashi
Lei
Zhou
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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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CD1383: Collaborative Estimation for Robotic Manipulators
MERL is seeking a highly skilled and self-motivated intern to conduct research on condition monitoring for robotic manipulators. The ideal candidate should have solid backgrounds in robotic manipulators, stochastic estimation methods for dynamical systems, and collaborative strategies over multi-agents. Experience of applying machine learning to dynamical systems is a strong plus. Excellent coding skill and strong publication records are necessary. Senior Ph.D. students in control, robotics, or related areas are encouraged to apply. Start date for this internship is flexible, and the expected duration is about 3 months.
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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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SP1371: Object Tracking and Perception for Autonomous Driving
The Signal Processing (SP) group at MERL is seeking a highly motivated intern to conduct fundamental research in automotive radar-based object tracking and perception for autonomous driving. Previous experience on multiple (point and extended) object tracking, data association, and data-driven object detection/tracking is highly preferred. Knowledge about automotive radar schemes (MIMO array and waveform modulation (FMCW, PMCW, and OFDM)) and hands-on experience on open automotive datasets are a plus. Knowledge on vehicle dynamics is an asset. The intern will collaborate with a small group of MERL researchers to develop novel algorithms, conduct field measurements, data analysis (Python & MATLAB), and prepare results for patents and publication. Senior Ph.D. students with research focuses on signal processing, machine learning, optimization, applied mathematics, or related areas are encouraged to apply. The expected duration of the internship is 3 months with a flexible start date.
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Openings
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Recent Publications
- , "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}
- }
- , "Finite-Time Convergence of Continuous-Time Optimization Algorithms via Differential Inclusions", Advances in Neural Information Processing Systems (NIPS)- Workshop, January 2020.
- , "Model-based deep reinforcement learning for CACC in mixed-autonomy vehicle platoons", IEEE Conference on Decision and Control (CDC), December 2019.BibTeX Download PDFAbout TR2019-142
- @inproceedings{Chu2019dec,
- author = {Chu, Tianshu and Kalabić, Uroš},
- title = {Model-based deep reinforcement learning for CACC in mixed-autonomy vehicle platoons},
- booktitle = {IEEE Conference on Decision and Control (CDC)},
- year = 2019,
- month = dec,
- url = {https://www.merl.com/publications/TR2019-142}
- }
- , "Nonlinear Optimal Control Strategies for Buoyancy-Driven Flows in the Built Environment", Journal of Computers and Fluids, DOI: 10.1016/j.compfluid.2019.104313, Vol. 194, No. 104313, December 2019.BibTeX Download PDFAbout TR2019-151
- @article{Nabi2019dec,
- author = {Nabi, Saleh and Grover, Piyush and Caulfield, Colm},
- title = {Nonlinear Optimal Control Strategies for Buoyancy-Driven Flows in the Built Environment},
- journal = {Journal of Computers and Fluids},
- year = 2019,
- volume = 194,
- number = 104313,
- month = dec,
- doi = {10.1016/j.compfluid.2019.104313},
- url = {https://www.merl.com/publications/TR2019-151}
- }
- , "Improving LiDAR performance on complex terrain using CFD-based correction and direct-adjoint-loop optimization", Journal of physics, November 2019.BibTeX Download PDFAbout TR2019-152
- @article{Nabi2019nov,
- author = {Nabi, S. and Nishio, N. and Grover, P. and Matai, R. and Kajiyama, Y. and Kotake, N. and Kameyama, S. and Yoshiki, W. and Iida, M.},
- title = {Improving LiDAR performance on complex terrain using CFD-based correction and direct-adjoint-loop optimization},
- journal = {Journal of physics},
- year = 2019,
- month = nov,
- url = {https://www.merl.com/publications/TR2019-152}
- }
- , "Improving LiDAR performance on a complex terrain using CFD-based correction and direct-adjoint-loop optimization", NAWEA/WindTech Conference, October 2019.BibTeX Download PDFAbout TR2019-130
- @inproceedings{Nabi2019oct,
- author = {Nabi, Saleh and Grover, Piyush},
- title = {Improving LiDAR performance on a complex terrain using CFD-based correction and direct-adjoint-loop optimization},
- booktitle = {NAWEA/WindTech Conference},
- year = 2019,
- month = oct,
- url = {https://www.merl.com/publications/TR2019-130}
- }
- , "DEES: A Class of Data-Enabled Robust Feedback Algorithms for Real-Time Optimization", IFAC Nonlinear Control Systems (NOLCOS), September 2019.BibTeX Download PDFAbout TR2019-095
- @inproceedings{Poveda2019sep,
- author = {Poveda, Jorge and Vamvoudakis, Kyriakos and Benosman, Mouhacine},
- title = {DEES: A Class of Data-Enabled Robust Feedback Algorithms for Real-Time Optimization},
- booktitle = {IFAC Nonlinear Control Systems (NOLCOS)},
- year = 2019,
- month = sep,
- url = {https://www.merl.com/publications/TR2019-095}
- }
- , "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.
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