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


    See All News & Events for Dynamical Systems
  • Internships

    • 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.

    • CA1646: Path Planning and Model Predictive Control for Autonomous Vehicles

      MERL is seeking highly motivated and qualified interns to collaborate on the implementation and experimental validation of algorithms for path/motion planning and optimization-based tracking control in autonomous vehicles. An ideal candidate should have experience in path planning and/or model predictive control (MPC) for autonomous vehicles, and the candidate should be familiar with Matlab and Simulink. Any experience with dSPACE (e.g., MicroAutoBox) or C/C++ code generation is a plus. Both MS and PhD students are welcome to apply. Start date for this internship is as soon as possible, and the expected duration is about 3 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.

    • 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
  • Recent Publications

    •  Quirynen, R., Berntorp, K., "Uncertainty Propagation by Linear Regression Kalman Filters for Stochastic NMPC", IFAC Conference on Nonlinear Model Predictive Control, July 2021.
      BibTeX TR2021-084 PDF
      • @inproceedings{Quirynen2021jul,
      • author = {Quirynen, Rien and Berntorp, Karl},
      • title = {Uncertainty Propagation by Linear Regression Kalman Filters for Stochastic NMPC},
      • booktitle = {IFAC Conference on Nonlinear Model Predictive Control},
      • year = 2021,
      • month = jul,
      • url = {https://www.merl.com/publications/TR2021-084}
      • }
    •  Aguilar Marsillach, D., Di Cairano, S., Kalabic, U., Weiss, A., "Fail-Safe Spacecraft Rendezvous on Near-Rectilinear Halo Orbits", American Control Conference (ACC), May 2021.
      BibTeX TR2021-054 PDF
      • @inproceedings{AguilarMarsillach2021may,
      • author = {Aguilar Marsillach, Daniel and Di Cairano, Stefano and Kalabic, Uros and Weiss, Avishai},
      • title = {Fail-Safe Spacecraft Rendezvous on Near-Rectilinear Halo Orbits},
      • booktitle = {American Control Conference (ACC)},
      • year = 2021,
      • month = may,
      • url = {https://www.merl.com/publications/TR2021-054}
      • }
    •  Berntorp, K., Chakrabarty, A., Di Cairano, S., "Vehicle Center-of-Gravity Height and Dynamics Estimation with Uncertainty Quantification by Marginalized Particle Filter", American Control Conference (ACC), May 2021.
      BibTeX TR2021-058 PDF
      • @inproceedings{Berntorp2021may,
      • author = {Berntorp, Karl and Chakrabarty, Ankush and Di Cairano, Stefano},
      • title = {Vehicle Center-of-Gravity Height and Dynamics Estimation with Uncertainty Quantification by Marginalized Particle Filter},
      • booktitle = {American Control Conference (ACC)},
      • year = 2021,
      • month = may,
      • url = {https://www.merl.com/publications/TR2021-058}
      • }
    •  Berntorp, K., Quirynen, R., Vaskov, S., "Joint Tire-Stiffness and Vehicle-Inertial Parameter Estimation for Improved Predictive Control", American Control Conference, May 2021.
      BibTeX TR2021-060 PDF
      • @inproceedings{Berntorp2021may2,
      • author = {Berntorp, Karl and Quirynen, Rien and Vaskov, Sean},
      • title = {Joint Tire-Stiffness and Vehicle-Inertial Parameter Estimation for Improved Predictive Control},
      • booktitle = {American Control Conference},
      • year = 2021,
      • month = may,
      • url = {https://www.merl.com/publications/TR2021-060}
      • }
    •  Kalur, A., Nabi, S., Benosman, M., "Robust Adaptive Dynamic Mode Decomposition for Reduce Order Modelling of Partial Differential Equations", American Control Conference (ACC), May 2021.
      BibTeX TR2021-059 PDF
      • @inproceedings{Kalur2021may,
      • author = {Kalur, Aniketh and Nabi, Saleh and Benosman, Mouhacine},
      • title = {Robust Adaptive Dynamic Mode Decomposition for Reduce Order Modelling of Partial Differential Equations},
      • booktitle = {American Control Conference (ACC)},
      • year = 2021,
      • month = may,
      • url = {https://www.merl.com/publications/TR2021-059}
      • }
    •  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}
      • }
    See All Publications for Dynamical Systems
  • Videos