TR2024-076

Robust Parameter Estimation for Hybrid Dynamical Systems with Linear Parametric Uncertainty


    •  Johnson, R.S., Di Cairano, S., Sanfelice, R., "Robust Parameter Estimation for Hybrid Dynamical Systems with Linear Parametric Uncertainty", Automatica, DOI: 10.1016/​j.automatica.2024.111766, June 2024.
      BibTeX TR2024-076 PDF
      • @article{Johnson2024jun,
      • author = {Johnson, Ryan S. and Di Cairano, Stefano and Sanfelice, Ricardo}},
      • title = {Robust Parameter Estimation for Hybrid Dynamical Systems with Linear Parametric Uncertainty},
      • journal = {Automatica},
      • year = 2024,
      • month = jun,
      • doi = {10.1016/j.automatica.2024.111766},
      • url = {https://www.merl.com/publications/TR2024-076}
      • }
  • MERL Contact:
  • Research Areas:

    Control, Dynamical Systems, Signal Processing

Abstract:

We consider the problem of estimating a vector of unknown constant parameters for a class of hybrid dynamical systems – that is, systems whose state variables exhibit both continuous (flow) and discrete (jump) evolution – with dynamics that depend linearly on the unknown parameters. Using a hybrid systems framework, we propose a hybrid estimation algorithm that can operate during both flows and jumps that, under a notion of hybrid persistence of excitation, guarantees convergence of the parameter estimate to the true value. Furthermore, we show that the parameter estimate is input-to-state stable with respect to a class of hybrid disturbances. Simulation results including a spacecraft application show the merits of our proposed approach.