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
Avishai
Weiss
Karl
Berntorp
Christopher
Laughman
Uroš
Kalabić
Saleh
Nabi
Hongtao
Qiao
Rien
Quirynen
Daniel
Nikovski
Abraham
Goldsmith
Petros
Boufounos
Devesh
Jha
Hassan
Mansour
Diego
Romeres
Ankush
Chakrabarty
Chungwei
Lin
Yanting
Ma
Hongbo
Sun
William
Yerazunis
Jinyun
Zhang
Norihiro
Nishiuma
Abraham
P. Vinod
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News & Events
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EVENT MERL Virtual Open House 2020 Date & Time: Wednesday, December 9, 2020; 1:00-5:00PM EST
MERL Contacts: Elizabeth Phillips; Jeroen van Baar; Anthony Vetro
Location: Virtual
Research Areas: Applied Physics, Artificial Intelligence, Communications, Computational Sensing, Computer Vision, Control, Data Analytics, Dynamical Systems, Electric Systems, Electronic and Photonic Devices, Machine Learning, Multi-Physical Modeling, Optimization, Robotics, Signal Processing, Speech & AudioBrief- MERL will host a virtual open house on December 9, 2020. Live sessions will be held from 1-5pm EST, including an overview of recent activities by our research groups and a talk by Prof. Pierre Moulin of University of Illinois at Urbana-Champaign on adversarial machine learning. Registered attendees will also be able to browse our virtual booths at their convenience and connect with our research staff on engagement opportunities including internship, post-doc and research scientist openings, as well as visiting faculty positions.
Registration: https://mailchi.mp/merl/merl-virtual-open-house-2020
Schedule: https://www.merl.com/events/voh20
Current internship and employment openings:
https://www.merl.com/internship/openings
https://www.merl.com/employment/employment
Information about working at MERL:
https://www.merl.com/employment
- MERL will host a virtual open house on December 9, 2020. Live sessions will be held from 1-5pm EST, including an overview of recent activities by our research groups and a talk by Prof. Pierre Moulin of University of Illinois at Urbana-Champaign on adversarial machine learning. Registered attendees will also be able to browse our virtual booths at their convenience and connect with our research staff on engagement opportunities including internship, post-doc and research scientist openings, as well as visiting faculty positions.
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NEWS Karl Berntorp gave an invited lecture at the Department of Electrical Engineering at Linkoping University Date: October 8, 2020
Where: Linkoping University
MERL Contact: Karl Berntorp
Research Areas: Control, Dynamical Systems, Robotics, Signal ProcessingBrief- MERL researcher Karl Berntorp was invited to give a lecture in the class "Autonomous vehicles – planning, control, and learning systems" at the Division of Vehicular Systems, Department of Electrical Engineering, Linkoping University. The course is for the engineering-program students at Linkoping University and gives a basic understanding of the available models, methods, and software libraries to work on autonomous vehicles, with particular focus on motion-planning and control methods. The invited lecture described the different system components and design of motion planning and predictive control methods targeted to autonomous driving.
See All News & Events for Dynamical Systems -
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Internships
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CA1531: Learning-based multi-agent motion planning
MERL is seeking a highly motivated intern to research multi-agent motion planning by combining optimization-based methods with machine learning. The ideal candidate is enrolled in a PhD program in Electrical, Mechanical, Aerospace Engineering, Robotics, Computer Science or related program, with prior experience in multi-agent motion planning, machine learning (especially supervised, reinforcement, and safe ML), and convex and non-convex optimization. A successful internship will result in innovative methods for multiagent planning, in the development of well-documented (Python/MATLAB) code for validating the proposed methods, and in the submission of relevant results for publication in peer-reviewed conference proceedings and journals. The expected duration of the internship is 3 months with a flexible start date in the Spring/Summer 2021. This internship is preferred to be onsite at MERL, but may be done remotely where you live if the COVID pandemic makes it necessary.
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SP1512: Mutual Interference Mitigation
The Signal Processing (SP) group at MERL is seeking a highly motivated intern to conduct fundamental research in mutual interference mitigation for automotive radar. Previous experience in waveform design, radar detection under interference, joint communication and sensing, interference mitigation, and deep learning for radar is highly preferred. Knowledge about automotive radar schemes (MIMO and waveform modulation, e.g., FMCW, PMCW, and OFDM) is a plus. The intern will collaborate with a small group of MERL researchers to develop novel algorithms, design experiments using MERL in-house testbed, 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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SP1542: Research in Computational Sensing
The Computational Sensing team at MERL is seeking motivated and qualified individuals to assist in the development of computational methods for a variety of sensing applications. Ideal candidates should be Ph.D. students and have solid background and publication record in any of the following, or related areas: imaging inverse problems, learning for inverse problems, large-scale optimization, blind inverse scattering, radar/lidar/sonar imaging, sensing of dynamical systems, or wave-based inversion. Experience with experimentally measured data is desirable. Publication of the results produced during our internships is expected. The duration of the internships is anticipated to be 3-6 months. Start date is flexible. This internship is preferred to be onsite at MERL, but may be done remotely where you live if the COVID pandemic makes it necessary.
See All Internships for Dynamical Systems -
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Recent Publications
- "Model Predictive Control Approach for Autonomous Sun-Synchronous Sub-Recurrent Orbit Control", AIAA SciTech, January 2021.BibTeX TR2021-005 PDF
- @inproceedings{Hayashi2021jan,
- author = {Hayashi, Naohiro and Weiss, Avishai and Di Cairano, Stefano},
- title = {Model Predictive Control Approach for Autonomous Sun-Synchronous Sub-Recurrent Orbit Control},
- booktitle = {AIAA SciTech},
- year = 2021,
- month = jan,
- url = {https://www.merl.com/publications/TR2021-005}
- }
, - "Data-Enabled Extremum Seeking: A Cooperative Concurrent Learning-Based Approach", International journal of adaptive control and signal processing, December 2020.BibTeX TR2020-180 PDF
- @article{Poveda2020dec,
- author = {Poveda, Jorge and Benosman, Mouhacine and Vamvoudakis, Kyriakos},
- title = {Data-Enabled Extremum Seeking: A Cooperative Concurrent Learning-Based Approach},
- journal = {International journal of adaptive control and signal processing},
- year = 2020,
- month = dec,
- url = {https://www.merl.com/publications/TR2020-180}
- }
, - "Abort-Safe Spacecraft Rendezvous in case of Partial Thrust Failure", IEEE Conference on Decision and Control (CDC), December 2020.BibTeX TR2020-175 PDF
- @inproceedings{AguilarMarsillach2020dec,
- author = {Aguilar Marsillach, Daniel and Di Cairano, Stefano and Weiss, Avishai},
- title = {Abort-Safe Spacecraft Rendezvous in case of Partial Thrust Failure},
- booktitle = {IEEE Conference on Decision and Control (CDC)},
- year = 2020,
- month = dec,
- url = {https://www.merl.com/publications/TR2020-175}
- }
, - "Electric Satellite Station Keeping, Attitude Control, and Momentum Management by MPC", IEEE Transactions on Control Systems Technology, December 2020.BibTeX TR2020-153 PDF
- @article{Caverly2020dec,
- author = {Caverly, Ryan and Di Cairano, Stefano and Weiss, Avishai},
- title = {Electric Satellite Station Keeping, Attitude Control, and Momentum Management by MPC},
- journal = {IEEE Transactions on Control Systems Technology},
- year = 2020,
- month = dec,
- url = {https://www.merl.com/publications/TR2020-153}
- }
, - "Stochastic optimal control formalism for an open quantum system", Physical Review, DOI: 10.1103/PhysRevA.102.052605, Vol. 102, pp. 052605, December 2020.BibTeX TR2020-163 PDF
- @article{Lin2020dec,
- author = {Lin, Chungwei and Sels, Dries and Ma, Yanting and Wang, Yebin},
- title = {Stochastic optimal control formalism for an open quantum system},
- journal = {Physical Review},
- year = 2020,
- volume = 102,
- pages = 052605,
- month = dec,
- doi = {10.1103/PhysRevA.102.052605},
- url = {https://www.merl.com/publications/TR2020-163}
- }
, - "Tracking neighboring quasi-satellite orbits around Phobos", World Congress of the International Federation of Automatic Control (IFAC), July 2020.BibTeX TR2020-102 PDF
- @inproceedings{Muralidharan2020jul,
- author = {Muralidharan, Vivek and Weiss, Avishai and Kalabic, Uros},
- title = {Tracking neighboring quasi-satellite orbits around Phobos},
- booktitle = {World Congress of the International Federation of Automatic Control (IFAC)},
- year = 2020,
- month = jul,
- url = {https://www.merl.com/publications/TR2020-102}
- }
, - "Control of traffic light timing using decentralized deep reinforcement learning", World Congress of the International Federation of Automatic Control (IFAC), July 2020.BibTeX TR2020-101 PDF
- @inproceedings{Maske2020jul,
- author = {Maske, Harshal and Chu, Tianshu and Kalabic, Uros},
- title = {Control of traffic light timing using decentralized deep reinforcement learning},
- booktitle = {World Congress of the International Federation of Automatic Control (IFAC)},
- year = 2020,
- month = jul,
- url = {https://www.merl.com/publications/TR2020-101}
- }
, - "Fail-safe Rendezvous Control on Elliptic Orbits using Reachable Sets", American Control Conference (ACC), DOI: 10.23919/ACC45564.2020.9147957, July 2020, pp. 4920-4925.BibTeX TR2020-098 PDF
- @inproceedings{AguilarMarsillach2020jul,
- author = {Aguilar Marsillach, Daniel and Di Cairano, Stefano and Weiss, Avishai},
- title = {Fail-safe Rendezvous Control on Elliptic Orbits using Reachable Sets},
- booktitle = {American Control Conference (ACC)},
- year = 2020,
- pages = {4920--4925},
- month = jul,
- publisher = {IEEE},
- doi = {10.23919/ACC45564.2020.9147957},
- issn = {2378-5861},
- isbn = {978-1-5386-8266-1},
- url = {https://www.merl.com/publications/TR2020-098}
- }
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- "Model Predictive Control Approach for Autonomous Sun-Synchronous Sub-Recurrent Orbit Control", AIAA SciTech, January 2021.
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