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

Alexander Katriniok; Erfan Shakhesi; W.P.M.H. Heemels

doi:10.1109/CDC49753.2023.10384157

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

Alexander Katriniok, Erfan Shakhesi, W.P.M.H. Heemels

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 language	English
Title of host publication	2023 62nd IEEE Conference on Decision and Control, CDC 2023
Publisher	Institute of Electrical and Electronics Engineers
Pages	3776-3783
Number of pages	8
ISBN (Electronic)	979-8-3503-0124-3
DOIs	https://doi.org/10.1109/CDC49753.2023.10384157
Publication status	Published - 19 Jan 2024
Event	62nd IEEE Conference on Decision and Control, CDC 2023 - Singapore, Singapore Duration: 13 Dec 2023 → 15 Dec 2023 Conference number: 62

Conference

Conference	62nd IEEE Conference on Decision and Control, CDC 2023
Abbreviated title	CDC 2023
Country/Territory	Singapore
City	Singapore
Period	13/12/23 → 15/12/23

Keywords

Model Predictive Control
Control Barrier Functions
Recursive feasibility
Lane Merging

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10.1109/CDC49753.2023.10384157

CDC23_Katriniok_NMPC_CBFFinal author version , 587 KBLicence: CC BY-NC-ND
pdfFinal published version, 612 KBLicence: TAVERNE

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Katriniok, A., Shakhesi, E., & Heemels, W. P. M. H. (2024). Discrete-time Control Barrier Functions for Guaranteed Recursive Feasibility in Nonlinear MPC: An Application to Lane Merging. In 2023 62nd IEEE Conference on Decision and Control, CDC 2023 (pp. 3776-3783). Article 10384157 Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/CDC49753.2023.10384157

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Katriniok, A , Shakhesi, E & Heemels, WPMH 2024, Discrete-time Control Barrier Functions for Guaranteed Recursive Feasibility in Nonlinear MPC: An Application to Lane Merging. in 2023 62nd IEEE Conference on Decision and Control, CDC 2023., 10384157, Institute of Electrical and Electronics Engineers, pp. 3776-3783, 62nd IEEE Conference on Decision and Control, CDC 2023, Singapore, Singapore, 13/12/23. https://doi.org/10.1109/CDC49753.2023.10384157

Discrete-time Control Barrier Functions for Guaranteed Recursive Feasibility in Nonlinear MPC: An Application to Lane Merging. / Katriniok, Alexander ; Shakhesi, Erfan ; Heemels, W.P.M.H.
2023 62nd IEEE Conference on Decision and Control, CDC 2023. Institute of Electrical and Electronics Engineers, 2024. p. 3776-3783 10384157.

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

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

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