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.

  • Researchers

  • News & Events

    •  NEWS   Karl Berntorp gave an invited lecture at University of Houston
      Date: April 22, 2021
      Where: Houston, Texas
      MERL Contact: Karl Berntorp
      Research Areas: Control, Dynamical Systems, Robotics, Signal Processing
      Brief
      • The invited seminar "System Design, Planning, and Control for Autonomous Driving" was part of the Distinguished Seminar series at the Department of Mechanical Engineering at the University of Houston, Houston, Tx. The invited lecture described MERL research related to the different system components involved in autonomous driving, with particular focus on motion-planning and predictive-control methods.
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    •  NEWS   Karl Berntorp gave an invited lecture at the Department of Electrical Engineering at Linköping University
      Date: April 6, 2021
      Where: Linköping University, Sweden
      MERL Contact: Karl Berntorp
      Research Areas: Control, Dynamical Systems, Robotics
      Brief
      • MERL researcher Karl Berntorp was invited to give a lecture in the ELLIIT PhD course "Motion Planning and Control" at the Division of Vehicular Systems, Department of Electrical Engineering, Linköping University. The course is open for Ph.D. students as well as senior undergraduate students, and covers both fundamental algorithms and state-of-the-art methods for motion planning and control. The invited lecture described MERL research on the use of invariant sets for safe motion planning and control, with application to autonomous vehicles.
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  • Internships

    • 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.

    • CA1529: Energy Management for Electric Vehicles

      MERL is looking for a highly motivated intern to conduct research on data-driven energy management strategies for (hybrid) electric vehicles. The candidate will develop methods that use data, e.g., of human drivers or traffic conditions, in order to improve the control of electric vehicles. The ideal candidate will have experience in either one or multiple of the following topics: model predictive control, machine learning, statistical learning, numerical optimization, and (inverse) optimal control. Prior experience with (hybrid) electric vehicles is a plus. Good programming skills in MATLAB, Python, or C/C++ are required. PhD students in engineering or mathematics with a focus on control theory or numerical optimization are encouraged to apply. Publication of relevant results in conference proceedings or journals is expected. The expected duration of the internship is 3-6 months. The 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.

    • CA1530: Hybrid Control of Cyberphysical Systems

      MERL is seeking a highly motivated and qualified intern to collaborate with the Control for Autonomy team in the development of hybrid control algorithms for cyberphysical system. The potential subjects include formal methods for control synthesis, control barrier-functions, stabilizing control for hybrid dynamical systems, and optimal control of hybrid dynamics. The ideal candidate is expected to be working towards a PhD with strong emphasis in control theory, and to have interest and background in as many as possible among: predictive control, Lyapunov stability, formal methods for control, constrained control, optimization, and machine learning. Good programming skills in MATLAB, and/or Python are required. The expected duration of the internship is in the Spring of 2021, for a duration of 3-6 months. 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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  • Recent Publications

    •  Chiu, M., Kalabic, U., "Short Paper: Debt Representation in UTXO Blockchains", Financial Cryptography and Data Security, February 2021.
      BibTeX TR2021-014 PDF
      • @inproceedings{Chiu2021feb,
      • author = {Chiu, Michael and Kalabic, Uros},
      • title = {Short Paper: Debt Representation in UTXO Blockchains},
      • booktitle = {Financial Cryptography and Data Security},
      • year = 2021,
      • month = feb,
      • url = {https://www.merl.com/publications/TR2021-014}
      • }
    •  Hayashi, N., Weiss, A., Di Cairano, S., "Model Predictive Control Approach for Autonomous Sun-Synchronous Sub-Recurrent Orbit Control", AIAA SciTech, DOI: https:/​/​doi.org/​10.2514/​6.2021-1953, 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,
      • publisher = {AIAA},
      • doi = {https://doi.org/10.2514/6.2021-1953},
      • url = {https://www.merl.com/publications/TR2021-005}
      • }
    •  Poveda, J., Benosman, M., Vamvoudakis, K., "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}
      • }
    •  Aguilar Marsillach, D., Di Cairano, S., Weiss, A., "Abort-Safe Spacecraft Rendezvous in case of Partial Thrust Failure", IEEE Conference on Decision and Control (CDC), DOI: 10.1109/​CDC42340.2020.9303782, December 2020, pp. 1490-1495.
      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,
      • pages = {1490--1495},
      • month = dec,
      • publisher = {IEEE},
      • doi = {10.1109/CDC42340.2020.9303782},
      • url = {https://www.merl.com/publications/TR2020-175}
      • }
    •  Caverly, R., Di Cairano, S., Weiss, A., "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}
      • }
    •  Lin, C., Sels, D., Ma, Y., Wang, Y., "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}
      • }
    •  Danielson, C., Berntorp, K., Weiss, A., Di Cairano, S., "Robust Motion-Planning for Uncertain Systems with Disturbances using the Invariant-Set Motion-Planner", IEEE Transactions on Automatic Control, DOI: 10.1109/​TAC.2020.3008126, Vol. 65, No. 10, pp. 4456-4463, July 2020.
      BibTeX TR2021-038 PDF
      • @article{Danielson2020jul,
      • author = {Danielson, Claus and Berntorp, Karl and Weiss, Avishai and Di Cairano, Stefano},
      • title = {Robust Motion-Planning for Uncertain Systems with Disturbances using the Invariant-Set Motion-Planner},
      • journal = {IEEE Transactions on Automatic Control},
      • year = 2020,
      • volume = 65,
      • number = 10,
      • pages = {4456--4463},
      • month = jul,
      • doi = {10.1109/TAC.2020.3008126},
      • url = {https://www.merl.com/publications/TR2021-038}
      • }
    •  Muralidharan, V., Weiss, A., Kalabic, U., "Tracking neighboring quasi-satellite orbits around Phobos", World Congress of the International Federation of Automatic Control (IFAC), Rolf Findeisen, Sandra Hirche, Klaus Janschek, Martin Mönnigmann, Eds., DOI: 10.1016/​j.ifacol.2020.12.1952, July 2020, pp. 14906–14911.
      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,
      • editor = {Rolf Findeisen, Sandra Hirche, Klaus Janschek, Martin Mönnigmann},
      • pages = {14906–14911},
      • month = jul,
      • publisher = {Elsevier},
      • doi = {10.1016/j.ifacol.2020.12.1952},
      • url = {https://www.merl.com/publications/TR2020-102}
      • }
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  • Videos