A Nonlinear Model Predictive Control for Automated Drifting with a Standard Passenger Vehicle

Stan Meijer*, Alberto Bertipaglia, Barys Shyrokau

*Corresponding author for this work

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

Abstract

This paper presents a novel approach to automated drifting with a standard passenger vehicle, which involves a Nonlinear Model Predictive Control to stabilise and maintain the vehicle at high sideslip angle conditions. The proposed controller architecture is split into three components. The first part consists of the offline computed equilibrium maps, which provide the equilibrium points for each vehicle state given the desired sideslip angle and radius of the path. The second is the predictive controller minimising the errors between the equilibrium and actual vehicle states. The third is a path-following controller, which reduces the path error, altering the equilibrium curvature path. In a high-fidelity simulation environment, we validate the controller architecture capacity to stabilise the vehicle in automated drifting along a desired path, with a maximal lateral path deviation of 1 m. In the experiments with a standard passenger vehicle, we demonstrate that the proposed approach is capable of bringing and maintaining the vehicle at the desired 30 deg sideslip angle in both high and low friction conditions.

Original languageEnglish
Title of host publicationProceedings of the IEEE International Conference on Advanced Intelligent Mechatronics, AIM 2024
PublisherIEEE
Pages284-289
Number of pages6
ISBN (Electronic)979-8-3503-5536-9
DOIs
Publication statusPublished - 2024
Event2024 IEEE/ASME International Conference on Advanced Intelligent Mechatronics, AIM 2024 - Boston, United States
Duration: 15 Jul 202419 Jul 2024

Publication series

NameIEEE/ASME International Conference on Advanced Intelligent Mechatronics, AIM
ISSN (Print)2159-6247
ISSN (Electronic)2159-6255

Conference

Conference2024 IEEE/ASME International Conference on Advanced Intelligent Mechatronics, AIM 2024
Country/TerritoryUnited States
CityBoston
Period15/07/2419/07/24

Bibliographical note

Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care
Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

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