Risk-Bounded Control Using Stochastic Barrier Functions

Shakiba Yaghoubi, Keyvan Majd, Georgios Fainekos, Tomoya Yamaguchi, Danil Prokhorov, Bardh Hoxha

Research output: Contribution to journalArticlepeer-review

Abstract

In this letter, we design real-time controllers that react to uncertainties with stochastic characteristics and bound the probability of a failure in finite-time to a given desired value. Stochastic control barrier functions are used to derive sufficient conditions on the control input that bound the probability that the states of the system enter an unsafe region within a finite time. These conditions are combined with reachability conditions and used in an optimization problem to find the required control actions that lead the system to a goal set. We illustrate our theoretical development using a simulation of a lane-changing scenario in a highway with dense traffic.

Original languageEnglish (US)
Article number9286497
Pages (from-to)1831-1836
Number of pages6
JournalIEEE Control Systems Letters
Volume5
Issue number5
DOIs
StatePublished - Nov 2021

Keywords

  • Barrier function
  • robotics
  • uncertainty

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Control and Optimization

Fingerprint

Dive into the research topics of 'Risk-Bounded Control Using Stochastic Barrier Functions'. Together they form a unique fingerprint.

Cite this