NEWS  |  MERL Researcher Ankush Chakrabarty organized a special session on data-driven control at IEEE CCTA 2020

Date released: August 25, 2020


  •  NEWS   MERL Researcher Ankush Chakrabarty organized a special session on data-driven control at IEEE CCTA 2020
  • Date:

    August 25, 2020

  • Description:

    Ankush Chakrabarty co-organized an invited session on “Data-Driven Control For Industrial Applications” at the IEEE Conference on Control Technology and Applications with Shahin Shahrampour (Asst. Prof., Texas A&M). Talks covered topics including reinforcement learning for aerospace systems, constrained reinforcement learning for motors, deep Q learning for traffic systems and participants included speakers from Stanford University, North Carolina State University, Texas A&M, Oklahoma State University, University of Science and Technology at Beijing, and TU Delft.

    MERL presented research (Chakrabarty, Danielson, Wang) on constraint-enforcing output-tracking with approximate dynamic programming for servomotor systems.

  • MERL Contact:
  • Research Areas:

    Artificial Intelligence, Control, Data Analytics, Dynamical Systems, Machine Learning, Optimization, Robotics

    •  Chakrabarty, A., Danielson, C., Wang, Y., "Data-Driven Optimal Tracking with Constrained Approximate Dynamic Programming for Servomotor Systems", IEEE Conference on Control Technology and Applications, August 2020.
      BibTeX TR2020-116 PDF
      • @inproceedings{Chakrabarty2020aug,
      • author = {Chakrabarty, Ankush and Danielson, Claus and Wang, Yebin},
      • title = {Data-Driven Optimal Tracking with Constrained Approximate Dynamic Programming for Servomotor Systems},
      • booktitle = {IEEE Conference on Control Technology and Applications},
      • year = 2020,
      • month = aug,
      • url = {https://www.merl.com/publications/TR2020-116}
      • }