Event Triggered Control and Estimation

Sensing and communication for autonomous sytsems can be demanding in terms of energy and communication consumption. This problem is amplfied when considering teams of autonomous systems where it may be unreasonable to expect agents to continusouly communicate with other agents. Event-triggered control strategies take a more opportunistic approach for control and estimation of dynamical systems. In a multi-agent setting, agents may not need to communicate continuously in order to sovle the group task. Our research explores how event triggering strategies can be used to solve cooperative control and estimation problems. We consider bearing-based formation control problem, distributed Kalman filtering, and synchronization problems using event or asynchronous strategies.

Kalman Event Triggered Filter Event triggered formation control Asynchronous synchronization

Related Publications:

  1. G. Barkai, L. Mirkin, and D. Zelazo, “Asynchronous Sampled-Data Synchronization with Small Communications Delays,” in IEEE Conference on Decision and Control, Milan, Italy, Dec. 2024.
    Barkai2024_CDC.pdf Barkai2024_CDC.slides DOI: 10.1109/CDC56724.2024.10886376 Barkai2024_CDC.bibtex
  2. G. Barkai, L. Mirkin, and D. Zelazo, “An Emulation Approach to Output-Feedback Sampled-Data Synchronization,” in European Control Conference, Stockholm, Sweden, Jun. 2024.
    Barkai2024_ECC.pdf Barkai2024_ECC.slides Barkai2024_ECC.bibtex
  3. G. Barkai, L. Mirkin, and D. Zelazo, “Asynchronous Sampled-Data Synchronization with Small communication Delays,” in 63rd Israel Annual Conference on Aerospace Sciences, Haifa, Israel, May 2024.
    Barkai_IACAS2024.pdf Barkai_IACAS2024.bibtex
  4. M. Sewlia and D. Zelazo, “Bearing-Based Formation Stabilization Using Event-Triggered Control,” International Journal on Robust and Nonlinear Control, 34(6):4375–4387, 2024.
    Sewlia2023a_J.pdf DOI: 10.1002/rnc.7185 Sewlia2023a_J.bibtex
  5. G. Barkai, L. Mirkin, and D. Zelazo, “An emulation approach to sampled-data synchronization,” in IEEE Conference on Decision and Control, Singapore, Dec. 2023.
    Barkai2023a.pdf DOI: 10.1109/cdc49753.2023.10384079 Barkai2023a.bibtex
  6. A. Priel and D. Zelazo, “Distributed Consensus Kalman Filtering Over Time-Varying Graphs,” in IFAC World Congress, Yokohama, Japan, Jul. 2023.
    Priel2023a_C.pdf DOI: 10.1016/j.ifacol.2023.10.903 Priel2023a_C.poster Priel2023a_C.bibtex
  7. A. Priel and D. Zelazo, “Event-triggered consensus Kalman filtering for time-varying networks and intermittent observations,” International Journal of Robust and Nonlinear Control, 33(13):7430–7451, 2023.
    Priel2023_J.pdf DOI: https://doi.org/10.1002/rnc.6762 Priel2023_J.bibtex
  8. A. Priel, “Consensus Kalman Filtering: Filter Design and Event-Triggering,” mastersthesis, Technion - Israel Institute of Technology, Aerospace Engineering Department, 2022.
    Priel2022.pdf Priel2022.bibtex
  9. A. Priel and D. Zelazo, “An Improved Distributed Consensus Kalman Filter Design Approach,” in IEEE Conference on Decision and Control, Austin, Texas, Dec. 2021.
    Priel2021a.pdf Priel2021a.slides DOI: 10.1109/cdc45484.2021.9683438 Priel2021a.bibtex
  10. M. Sewlia, “Distributed Event-Triggered Control for Multi-Agent Systems with Second-Order Dynamics,” mastersthesis, Technion - Israel Institute of Technology, Aerospace Engineering Department, 2020.
    Sewlia2020.pdf Sewlia2020.bibtex
  11. M. Sewlia and D. Zelazo, “Distributed Event-Based Control for Second-Order Multi-Agent Systems,” in 27th Mediterranean Conference on Control and Automation, Akko, Israel, Jul. 2019.
    Sewlia2019a.pdf DOI: 10.1109/med.2019.8798577 Sewlia2019a.bibtex