Strong Invariance Using Control Barrier Functions: A Clarke Tangent Cone Approach.

Abstract

Many control applications require that a system be constrained to a particular set of states, often termed as safe set. A practical and flexible method for rendering safe sets forward-invariant involves computing control input using Control Barrier Functions and Quadratic Programming methods. Many prior results however require the resulting control input to be continuous, which requires strong assumptions or can be difficult to demonstrate theoretically. In this paper we use differential inclusion methods to show that simultaneously rendering multiple sets invariant can be accomplished using a discontinuous control input. We present an optimization formulation which computes such control inputs and which can be posed in multiple forms, including a feasibility problem, a linear program, or a quadratic program. In addition, we discuss conditions under which the optimization problem is feasible and show that any feasible solution of the considered optimization problem which is measurable renders the multiple safe sets forward invariant.

Bib

@inproceedings{DBLP:conf/cdc/UsevitchGP20,
  author       = {James Usevitch and
                  Kunal Garg and
                  Dimitra Panagou},
  title        = {Strong Invariance Using Control Barrier Functions: {A} Clarke Tangent
                  Cone Approach},
  booktitle    = {59th {IEEE} Conference on Decision and Control, {CDC} 2020, Jeju Island,
                  South Korea, December 14-18, 2020},
  pages        = {2044--2049},
  publisher    = {{IEEE}},
  year         = {2020},
  url          = {https://doi.org/10.1109/CDC42340.2020.9303873},
  doi          = {10.1109/CDC42340.2020.9303873},
  timestamp    = {Fri, 04 Mar 2022 13:31:02 +0100},
  biburl       = {https://dblp.org/rec/conf/cdc/UsevitchGP20.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}