Model Predictive Control-Based Integrated Path Tracking and Velocity Control for Autonomous Vehicle with Four-Wheel Independent Steering and Driving

This paper presents an MPC-based integrated control algorithm for an autonomous vehicle equipped with four-wheel independent steering and driving systems. The objective of this research is to improve the performance of the path and velocity tracking controllers by distributing the control effort to...

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Autores principales:	Yonghwan Jeong, Seongjin Yim
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	autonomous vehicles four-wheel independent steering four-wheel independent driving model predictive control control allocation path tracking Electronics TK7800-8360
Acceso en línea:	https://doaj.org/article/2a196e33b392467d9b5e9e4e21f62d81
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spelling	oai:doaj.org-article:2a196e33b392467d9b5e9e4e21f62d812021-11-25T17:24:51ZModel Predictive Control-Based Integrated Path Tracking and Velocity Control for Autonomous Vehicle with Four-Wheel Independent Steering and Driving10.3390/electronics102228122079-9292https://doaj.org/article/2a196e33b392467d9b5e9e4e21f62d812021-11-01T00:00:00Zhttps://www.mdpi.com/2079-9292/10/22/2812https://doaj.org/toc/2079-9292This paper presents an MPC-based integrated control algorithm for an autonomous vehicle equipped with four-wheel independent steering and driving systems. The objective of this research is to improve the performance of the path and velocity tracking controllers by distributing the control effort to the multiple actuators. The proposed algorithm has two modules: reference state decision and MPC-based vehicle motion controller. Reference state decision module determines reference state profiles consisting of yaw rate and velocity in order to overcome the limitation of the error dynamics-based path tracking controller, which requires several assumptions on the reference path. The MPC-based vehicle motion controller is designed with a linear time-varying vehicle model in order to optimally allocate the control effort to each actuator. A linear time-varying MPC is adopted to reduce computational burden caused by using a non-linear one. The effectiveness of the proposed algorithm is validated via simulation on MATLAB/Simulink and CarSim. The simulation results show that the proposed algorithm improves the reference tracking performance by effectively distributing the control effort to the steering angle and driving force of each actuator.Yonghwan JeongSeongjin YimMDPI AGarticleautonomous vehiclesfour-wheel independent steeringfour-wheel independent drivingmodel predictive controlcontrol allocationpath trackingElectronicsTK7800-8360ENElectronics, Vol 10, Iss 2812, p 2812 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	autonomous vehicles four-wheel independent steering four-wheel independent driving model predictive control control allocation path tracking Electronics TK7800-8360
spellingShingle	autonomous vehicles four-wheel independent steering four-wheel independent driving model predictive control control allocation path tracking Electronics TK7800-8360 Yonghwan Jeong Seongjin Yim Model Predictive Control-Based Integrated Path Tracking and Velocity Control for Autonomous Vehicle with Four-Wheel Independent Steering and Driving
description	This paper presents an MPC-based integrated control algorithm for an autonomous vehicle equipped with four-wheel independent steering and driving systems. The objective of this research is to improve the performance of the path and velocity tracking controllers by distributing the control effort to the multiple actuators. The proposed algorithm has two modules: reference state decision and MPC-based vehicle motion controller. Reference state decision module determines reference state profiles consisting of yaw rate and velocity in order to overcome the limitation of the error dynamics-based path tracking controller, which requires several assumptions on the reference path. The MPC-based vehicle motion controller is designed with a linear time-varying vehicle model in order to optimally allocate the control effort to each actuator. A linear time-varying MPC is adopted to reduce computational burden caused by using a non-linear one. The effectiveness of the proposed algorithm is validated via simulation on MATLAB/Simulink and CarSim. The simulation results show that the proposed algorithm improves the reference tracking performance by effectively distributing the control effort to the steering angle and driving force of each actuator.
format	article
author	Yonghwan Jeong Seongjin Yim
author_facet	Yonghwan Jeong Seongjin Yim
author_sort	Yonghwan Jeong
title	Model Predictive Control-Based Integrated Path Tracking and Velocity Control for Autonomous Vehicle with Four-Wheel Independent Steering and Driving
title_short	Model Predictive Control-Based Integrated Path Tracking and Velocity Control for Autonomous Vehicle with Four-Wheel Independent Steering and Driving
title_full	Model Predictive Control-Based Integrated Path Tracking and Velocity Control for Autonomous Vehicle with Four-Wheel Independent Steering and Driving
title_fullStr	Model Predictive Control-Based Integrated Path Tracking and Velocity Control for Autonomous Vehicle with Four-Wheel Independent Steering and Driving
title_full_unstemmed	Model Predictive Control-Based Integrated Path Tracking and Velocity Control for Autonomous Vehicle with Four-Wheel Independent Steering and Driving
title_sort	model predictive control-based integrated path tracking and velocity control for autonomous vehicle with four-wheel independent steering and driving
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/2a196e33b392467d9b5e9e4e21f62d81
work_keys_str_mv	AT yonghwanjeong modelpredictivecontrolbasedintegratedpathtrackingandvelocitycontrolforautonomousvehiclewithfourwheelindependentsteeringanddriving AT seongjinyim modelpredictivecontrolbasedintegratedpathtrackingandvelocitycontrolforautonomousvehiclewithfourwheelindependentsteeringanddriving
_version_	1718412397960495104

Model Predictive Control-Based Integrated Path Tracking and Velocity Control for Autonomous Vehicle with Four-Wheel Independent Steering and Driving

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