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Discrete-time Control Barrier Functions for Guaranteed Recursive Feasibility in Nonlinear MPC: An Application to Lane Merging

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

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Abstract

In this paper, we present conditions under which the terminal ingredients, defined by discrete-time control barrier function (DTCBF) certificates, guarantee recursive feasibility in nonlinear MPC. Further, we introduce the notion of quasi-DTCBF (qDTCBF) certificates. Compared to DTCBFs, qDTCBF conditions can be satisfied with tighter control input bounds, which is highly advantageous if only limited actuation
is possible. Both certificates encourage an earlier reaction of the control system and result in a lower cumulative MPC cost. The methodology is applied to a lane merging problem in automated driving, in which DTCBF and qDTCBF certificates subject to
input constraints form the terminal ingredients to guarantee recursive feasibility of the nonlinear MPC scheme. A simulation study demonstrates the efficacy of the concept.
Original languageEnglish
Title of host publication2023 62nd IEEE Conference on Decision and Control, CDC 2023
PublisherInstitute of Electrical and Electronics Engineers
Pages3776-3783
Number of pages8
ISBN (Electronic)979-8-3503-0124-3
DOIs
Publication statusPublished - 19 Jan 2024
Event62nd IEEE Conference on Decision and Control, CDC 2023 - Singapore, Singapore
Duration: 13 Dec 2023 → 15 Dec 2023
Conference number: 62

Conference

Conference62nd IEEE Conference on Decision and Control, CDC 2023
Abbreviated titleCDC 2023
Country/TerritorySingapore
CitySingapore
Period13/12/23 → 15/12/23

Keywords

  • Model Predictive Control
  • Control Barrier Functions
  • Recursive feasibility
  • Lane Merging

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