NMPC-Based Path Tracking Control Through Cascaded Discretization Method Considering Handling Stability for 4WS Autonomous Vehicles Under Extreme Conditions

In the realm of autonomous driving, motion control generally involves two critical aspects—path following and stability control—and an inevitable mutual interference exists between them under extreme conditions. To tackle this challenge, this study proposes a collaborative approach of path tracking...

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Main Authors: Guozhu Zhu, Weirong Hong
Format: Article
Language:English
Published: MDPI AG 2024-12-01
Series:World Electric Vehicle Journal
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Online Access:https://www.mdpi.com/2032-6653/15/12/573
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author Guozhu Zhu
Weirong Hong
author_facet Guozhu Zhu
Weirong Hong
author_sort Guozhu Zhu
collection DOAJ
description In the realm of autonomous driving, motion control generally involves two critical aspects—path following and stability control—and an inevitable mutual interference exists between them under extreme conditions. To tackle this challenge, this study proposes a collaborative approach of path tracking and stability control. When designing the path tracking control module, the effects of vertical tire load transfer and road surface adhesion coefficients on tire force calculations were taken into account to mitigate vehicle dynamics model mismatch. Leveraging the receding horizon optimization characteristic of nonlinear model predictive control (NMPC), a cascaded discretization approach was utilized to realize a balance between precision and real-time performance in numerical solutions. Then, a stability controller, which employs rear wheel steering, was designed to prevent excessive increases in the vehicle’s sideslip angle, thereby ensuring the vehicle’s lateral stability. The effectiveness of the proposed strategy is validated through CarSim 8.0/Simulink cosimulation. The outcomes demonstrate that the stability controller significantly enhances vehicle stability under high-speed and low-adhesion conditions. On the premise of stability, the proposed path tracking controller has exhibited significant enhancements in real-time performance, without compromising the accuracy of path tracking.
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spelling doaj-art-ad8abc9f4ae341e6ac3d7dbdd6780f532025-08-20T02:01:19ZengMDPI AGWorld Electric Vehicle Journal2032-66532024-12-01151257310.3390/wevj15120573NMPC-Based Path Tracking Control Through Cascaded Discretization Method Considering Handling Stability for 4WS Autonomous Vehicles Under Extreme ConditionsGuozhu Zhu0Weirong Hong1College of Energy Engineering, Zhejiang University, Hangzhou 310027, ChinaCollege of Energy Engineering, Zhejiang University, Hangzhou 310027, ChinaIn the realm of autonomous driving, motion control generally involves two critical aspects—path following and stability control—and an inevitable mutual interference exists between them under extreme conditions. To tackle this challenge, this study proposes a collaborative approach of path tracking and stability control. When designing the path tracking control module, the effects of vertical tire load transfer and road surface adhesion coefficients on tire force calculations were taken into account to mitigate vehicle dynamics model mismatch. Leveraging the receding horizon optimization characteristic of nonlinear model predictive control (NMPC), a cascaded discretization approach was utilized to realize a balance between precision and real-time performance in numerical solutions. Then, a stability controller, which employs rear wheel steering, was designed to prevent excessive increases in the vehicle’s sideslip angle, thereby ensuring the vehicle’s lateral stability. The effectiveness of the proposed strategy is validated through CarSim 8.0/Simulink cosimulation. The outcomes demonstrate that the stability controller significantly enhances vehicle stability under high-speed and low-adhesion conditions. On the premise of stability, the proposed path tracking controller has exhibited significant enhancements in real-time performance, without compromising the accuracy of path tracking.https://www.mdpi.com/2032-6653/15/12/573autonomous vehiclespath trackingNMPCcascaded discretization methodstability control
spellingShingle Guozhu Zhu
Weirong Hong
NMPC-Based Path Tracking Control Through Cascaded Discretization Method Considering Handling Stability for 4WS Autonomous Vehicles Under Extreme Conditions
World Electric Vehicle Journal
autonomous vehicles
path tracking
NMPC
cascaded discretization method
stability control
title NMPC-Based Path Tracking Control Through Cascaded Discretization Method Considering Handling Stability for 4WS Autonomous Vehicles Under Extreme Conditions
title_full NMPC-Based Path Tracking Control Through Cascaded Discretization Method Considering Handling Stability for 4WS Autonomous Vehicles Under Extreme Conditions
title_fullStr NMPC-Based Path Tracking Control Through Cascaded Discretization Method Considering Handling Stability for 4WS Autonomous Vehicles Under Extreme Conditions
title_full_unstemmed NMPC-Based Path Tracking Control Through Cascaded Discretization Method Considering Handling Stability for 4WS Autonomous Vehicles Under Extreme Conditions
title_short NMPC-Based Path Tracking Control Through Cascaded Discretization Method Considering Handling Stability for 4WS Autonomous Vehicles Under Extreme Conditions
title_sort nmpc based path tracking control through cascaded discretization method considering handling stability for 4ws autonomous vehicles under extreme conditions
topic autonomous vehicles
path tracking
NMPC
cascaded discretization method
stability control
url https://www.mdpi.com/2032-6653/15/12/573
work_keys_str_mv AT guozhuzhu nmpcbasedpathtrackingcontrolthroughcascadeddiscretizationmethodconsideringhandlingstabilityfor4wsautonomousvehiclesunderextremeconditions
AT weironghong nmpcbasedpathtrackingcontrolthroughcascadeddiscretizationmethodconsideringhandlingstabilityfor4wsautonomousvehiclesunderextremeconditions