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

    • CA1260: Model Predictive Control of Hybrid Systems

      The Control and Dynamical Systems (CD) group at MERL is seeking a highly motivated intern to work on hybrid model predictive control. The scope of work includes the development of model predictive control algorithms for hybrid dynamical systems, switched systems, and quantized systems, analysis and property proving, and applications in automotive, space systems, and energy systems. PhD students with expertise in some among control, optimization, model predictive control and hybrid systems, and with working knowledge of Matlab implementation are welcome to apply. The expected duration of the internship is 3-6 months with flexible start date.

    • CA1470: Connected vehicle-based distributed learning and estimation of road conditions

      MERL is seeking a highly motivated qualified intern to collaborate with the Control for Autonomy team and the Signal Processing group in the development of learning technologies for Connected Vehicles technologies for distributed learning and estimation. The candidate will develop methods for distributed learning and estimation of road and road network conditions using information acquired from multiple connected vehicles. The ideal candidate is expected to be involved in research on collaborative distributed learning and estimation, with particular emphasis on statistical learning. The ideal candidate has knowledge of machine learning, estimation, connected vehicles and vehicle control systems. Knowledge of one or more traffic and/or multi-vehicle simulators (SUMO, Vissim, etc.) is a plus. Good programming skills in Matlab, Python, or C/C++ are required. Candidates in their senior year of Master, or junior or senior years of a Ph.D. program are encouraged to apply. The expected duration of the internship is for the Fall 2020 or Winter 2021, with start date in November 2020-January 2021. Part-time engagement may be considered, although full-time is preferred. Given the current situation with COVID-19 pandemic, this internship will be done remotely from where the candidates lives using MERL equipment and resources.

    • MD1406: Numerical Analysis of Electric Machines

      MERL is seeking a motivated and qualified intern to conduct research in the design, modeling and optimization of electrical machines. The ideal candidate should have solid backgrounds in electromagnetic theory, electric machine design, and numerical modeling techniques (including model reduction), research experiences in electric, magnetic, and thermal modeling and analysis of electrical machines, and demonstrated capability to publish results in leading conferences/journals. Experience with ANSYS, COMSOL, and optimization techniques is a strong plus. Senior Ph.D. students in electrical or mechanical engineering with related expertise are encouraged to apply. Start date for this internship is flexible and the duration is 3-6 months.


    See All Internships for Dynamical Systems
  • Recent Publications

    •  Muralidharan, V., Weiss, A., Kalabic, U., "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}
      • }
    •  Maske, H., Chu, T., Kalabic, U., "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}
      • }
    •  Aguilar Marsillach, D., Di Cairano, S., Weiss, A., "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}
      • }
    •  Vijayshankar, S., Nabi, S., Chakrabarty, A., Grover, P., Benosman, M., "Dynamic Mode Decomposition and Robust Estimation: Case Study of a 2D Turbulent Boussinesq Flow", American Control Conference (ACC), DOI: 10.23919/ACC45564.2020.9147823, July 2020, pp. 2351-2356.
      BibTeX TR2020-091 PDF
      • @inproceedings{Vijayshankar2020jul,
      • author = {Vijayshankar, Sanjana and Nabi, Saleh and Chakrabarty, Ankush and Grover, Piyush and Benosman, Mouhacine},
      • title = {Dynamic Mode Decomposition and Robust Estimation: Case Study of a 2D Turbulent Boussinesq Flow},
      • booktitle = {American Control Conference (ACC)},
      • year = 2020,
      • pages = {2351--2356},
      • month = jul,
      • publisher = {IEEE},
      • doi = {10.23919/ACC45564.2020.9147823},
      • issn = {2378-5861},
      • isbn = {978-1-5386-8266-1},
      • url = {https://www.merl.com/publications/TR2020-091}
      • }
    •  Tian, N., Fang, H., Wang, Y., "Real-Time Optimal Lithium-Ion Battery Charging Based on Explicit Model Predictive Control", IEEE Transactions on Industrial Informatics, DOI: 10.1109/TII.2020.2983176, June 2020.
      BibTeX TR2020-090 PDF
      • @article{Tian2020jun,
      • author = {Tian, Ning and Fang, Huazhen and Wang, Yebin},
      • title = {Real-Time Optimal Lithium-Ion Battery Charging Based on Explicit Model Predictive Control},
      • journal = {IEEE Transactions on Industrial Informatics},
      • year = 2020,
      • month = jun,
      • doi = {10.1109/TII.2020.2983176},
      • url = {https://www.merl.com/publications/TR2020-090}
      • }
    •  Kalabic, U., Grover, P., Aeron, S., "Optimization-based incentivization and control scheme for autonomous traffic", IEEE Intelligent Vehicle Symposium, June 2020.
      BibTeX TR2020-079 PDF
      • @inproceedings{Kalabic2020jun,
      • author = {Kalabic, Uros and Grover, Piyush and Aeron, Shuchin},
      • title = {Optimization-based incentivization and control scheme for autonomous traffic},
      • booktitle = {IEEE Intelligent Vehicle Symposium},
      • year = 2020,
      • month = jun,
      • url = {https://www.merl.com/publications/TR2020-079}
      • }
    •  Tian, N., Fang, H., Chen, J., Wang, Y., "Nonlinear Double-Capacitor Model for Rechargeable Batteries: Modeling, Identification and Validation", IEEE Transactions on Control Systems Technology, DOI: 10.1109/TCST.2020.2976036, pp. 1-15, April 2020.
      BibTeX TR2020-035 PDF
      • @article{Tian2020apr,
      • author = {Tian, Ning and Fang, Huazhen and Chen, Jian and Wang, Yebin},
      • title = {Nonlinear Double-Capacitor Model for Rechargeable Batteries: Modeling, Identification and Validation},
      • journal = {IEEE Transactions on Control Systems Technology},
      • year = 2020,
      • pages = {1--15},
      • month = apr,
      • doi = {10.1109/TCST.2020.2976036},
      • url = {https://www.merl.com/publications/TR2020-035}
      • }
    •  Laughman, C.R., Bortoff, S.A., "Nonlinear State Estimation with FMI: Tutorial and Applications", American Modelica Conference 2020, March 2020.
      BibTeX TR2020-031 PDF Software
      • @inproceedings{Laughman2020mar,
      • author = {Laughman, Christopher R. and Bortoff, Scott A.},
      • title = {Nonlinear State Estimation with FMI: Tutorial and Applications},
      • booktitle = {American Modelica Conference 2020},
      • year = 2020,
      • month = mar,
      • url = {https://www.merl.com/publications/TR2020-031}
      • }
    See All Publications for Dynamical Systems
  • Videos