Continuous Approximations of Projected Dynamical Systems via Control Barrier Functions

Giannis Delimpaltadakis (Corresponding author), Jorge Cortes, W.P.M.H. Heemels

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

Projected Dynamical Systems (PDSs) form a class of discontinuous constrained dynamical systems, and have been used widely to solve optimization problems and variational inequalities. Recently, they have also gained significant attention for control purposes, such as high-performance integrators, saturated control and feedback optimization. In this work, we establish that locally Lipschitz continuous dynamics, involving Control Barrier Functions (CBFs), namely CBF-based dynamics , approximate PDSs. Specifically, we prove that trajectories of CBF-based dynamics uniformly converge to trajectories of PDSs, as a CBF-parameter approaches infinity. Towards this, we also prove that CBF-based dynamics are perturbations of PDSs, with quantitative bounds on the perturbation. Our results pave the way to implement discontinuous PDS-based controllers in a continuous fashion, employing CBFs. We demonstrate this on an example on synchronverter control. Moreover, our results can be employed to numerically simulate PDSs, overcoming disadvantages of existing discretization schemes, such as computing projections to possibly non-convex sets. Finally, this bridge between CBFs and PDSs may yield other potential benefits, including novel insights on stability.

Original languageEnglish
Article number10645203
Pages (from-to)681-688
Number of pages8
JournalIEEE Transactions on Automatic Control
Volume70
Issue number1
Early online date23 Aug 2024
DOIs
Publication statusPublished - Jan 2025

Keywords

  • Control systems
  • Dynamical systems
  • Optimization
  • Perturbation methods
  • Power system dynamics
  • Trajectory
  • Vehicle dynamics
  • safety-critical control
  • discontinuous dynamical systems
  • Control barrier functions
  • synchronverters
  • projected dynamical systems
  • feedback optimization
  • nonsmooth dynamics

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