On full MAGV lateral dynamics exploitation: Autonomous Drift Control

Manuel Acosta; Stratis Kanarachos; Michael Fitzpatrick

doi:10.1109/AMC.2019.8371149

On full MAGV lateral dynamics exploitation: Autonomous Drift Control

Manuel Acosta, Stratis Kanarachos, Michael Fitzpatrick

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

2 Citations (Scopus)

Abstract

This paper explores the maximisation of the vehicle lateral dynamics on off-road conditions by means of active drifting and optimised wheel torque allocation. An Autonomous Drift Control (ADC) system based on a hierarchical control architecture is proposed to achieve this task. Specifically, the ADC consists of a high level layer that generates the state references and feedforward inputs to follow a reference path at a given body slip angle, and a low level Model Predictive Controller that coordinates the action of an Active Front Steering (AFS) system and four individual electric motors to track the upper level drift references. The performance of the proposed system is assessed in a Multi-Actuated Ground Vehicle (MAGV) using the simulation software IPG-CarMaker. Results evidence the ability of the proposed system to perform agile drifting manoeuvres. Essentially, the vehicle is able to follow tight road paths and maintain stability at high body slip angles, currently not feasible with other active safety technologie

Original language	English
Title of host publication	15th International Workshop on Advanced Motion Control (IEEE AMC2018), Tokyo
Publisher	IEEE
ISBN (Print)	9781538619452
DOIs	https://doi.org/10.1109/AMC.2019.8371149
Publication status	Published - 1 Mar 2018
Event	15th International Workshop on Advanced Motion Control - Tokyo, Japan Duration: 9 Mar 2018 → 11 Mar 2018 http://ewh.ieee.org/conf/amc/2018/

Publication series

Name
ISSN (Electronic)	1943-6580

Conference

Conference	15th International Workshop on Advanced Motion Control
Abbreviated title	IEEE AMC 2018
Country	Japan
City	Tokyo
Period	9/03/18 → 11/03/18
Internet address	http://ewh.ieee.org/conf/amc/2018/

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10.1109/AMC.2019.8371149

Cite this

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title = "On full MAGV lateral dynamics exploitation: Autonomous Drift Control",

abstract = "This paper explores the maximisation of the vehicle lateral dynamics on off-road conditions by means of active drifting and optimised wheel torque allocation. An Autonomous Drift Control (ADC) system based on a hierarchical control architecture is proposed to achieve this task. Specifically, the ADC consists of a high level layer that generates the state references and feedforward inputs to follow a reference path at a given body slip angle, and a low level Model Predictive Controller that coordinates the action of an Active Front Steering (AFS) system and four individual electric motors to track the upper level drift references. The performance of the proposed system is assessed in a Multi-Actuated Ground Vehicle (MAGV) using the simulation software IPG-CarMaker. Results evidence the ability of the proposed system to perform agile drifting manoeuvres. Essentially, the vehicle is able to follow tight road paths and maintain stability at high body slip angles, currently not feasible with other active safety technologie ",

author = "Manuel Acosta and Stratis Kanarachos and Michael Fitzpatrick",

year = "2018",

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doi = "10.1109/AMC.2019.8371149",

language = "English",

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publisher = "IEEE",

booktitle = "15th International Workshop on Advanced Motion Control (IEEE AMC2018), Tokyo",

address = "United States",

note = "15th International Workshop on Advanced Motion Control, IEEE AMC 2018 ; Conference date: 09-03-2018 Through 11-03-2018",

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T1 - On full MAGV lateral dynamics exploitation: Autonomous Drift Control

AU - Acosta, Manuel

AU - Kanarachos, Stratis

AU - Fitzpatrick, Michael

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Y1 - 2018/3/1

N2 - This paper explores the maximisation of the vehicle lateral dynamics on off-road conditions by means of active drifting and optimised wheel torque allocation. An Autonomous Drift Control (ADC) system based on a hierarchical control architecture is proposed to achieve this task. Specifically, the ADC consists of a high level layer that generates the state references and feedforward inputs to follow a reference path at a given body slip angle, and a low level Model Predictive Controller that coordinates the action of an Active Front Steering (AFS) system and four individual electric motors to track the upper level drift references. The performance of the proposed system is assessed in a Multi-Actuated Ground Vehicle (MAGV) using the simulation software IPG-CarMaker. Results evidence the ability of the proposed system to perform agile drifting manoeuvres. Essentially, the vehicle is able to follow tight road paths and maintain stability at high body slip angles, currently not feasible with other active safety technologie

AB - This paper explores the maximisation of the vehicle lateral dynamics on off-road conditions by means of active drifting and optimised wheel torque allocation. An Autonomous Drift Control (ADC) system based on a hierarchical control architecture is proposed to achieve this task. Specifically, the ADC consists of a high level layer that generates the state references and feedforward inputs to follow a reference path at a given body slip angle, and a low level Model Predictive Controller that coordinates the action of an Active Front Steering (AFS) system and four individual electric motors to track the upper level drift references. The performance of the proposed system is assessed in a Multi-Actuated Ground Vehicle (MAGV) using the simulation software IPG-CarMaker. Results evidence the ability of the proposed system to perform agile drifting manoeuvres. Essentially, the vehicle is able to follow tight road paths and maintain stability at high body slip angles, currently not feasible with other active safety technologie

U2 - 10.1109/AMC.2019.8371149

DO - 10.1109/AMC.2019.8371149

M3 - Conference proceeding

SN - 9781538619452

BT - 15th International Workshop on Advanced Motion Control (IEEE AMC2018), Tokyo

PB - IEEE

T2 - 15th International Workshop on Advanced Motion Control

Y2 - 9 March 2018 through 11 March 2018

ER -

On full MAGV lateral dynamics exploitation: Autonomous Drift Control

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