Trajectory tracking control for four-wheel independent drive intelligent vehicle based on model predictive control and sliding mode control

For four-wheel independent drive intelligent vehicle, the longitudinal and lateral motion control of the vehicle is decoupled and a hierarchical controller is designed: the upper layer is the motion controller, and the lower layer is the control distributor. In the motion controller, the model predi...

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Main Authors: HaiDong Wu, ZiHan Li, ZhenLi Si
Format: Article
Language:English
Published: SAGE Publishing 2021-09-01
Series:Advances in Mechanical Engineering
Online Access:https://doi.org/10.1177/16878140211045142
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spelling doaj-45cf523a0f054817bd5cdef9314c04852021-09-30T00:03:23ZengSAGE PublishingAdvances in Mechanical Engineering1687-81402021-09-011310.1177/16878140211045142Trajectory tracking control for four-wheel independent drive intelligent vehicle based on model predictive control and sliding mode controlHaiDong WuZiHan LiZhenLi SiFor four-wheel independent drive intelligent vehicle, the longitudinal and lateral motion control of the vehicle is decoupled and a hierarchical controller is designed: the upper layer is the motion controller, and the lower layer is the control distributor. In the motion controller, the model predictive control (MPC) is used to calculate the steering wheel angle and the total yaw moment for lateral control, and the sliding mode control (SMC) is used to calculate the total driving force for longitudinal control. In order to improve the control algorithm adaptability and the tracking accuracy at high speed, the UniTire model that can accurately express the complex coupling characteristics of tire under different working conditions are used and the numerical partial derivative of the state equation is used in MPC controller to ensure the feasibility of the algorithm. The control distributor distributes the total yaw moment and driving force calculated by the motion controller of the four wheels through the objective optimization function, and the constraints on road adhesion condition and the constraints on actuators are considered at the same time. A co-simulation platform is built in the CarSim/Simulink environment and the MPC-SMC controller is compared with the previously established MPC controller.https://doi.org/10.1177/16878140211045142
collection DOAJ
language English
format Article
sources DOAJ
author HaiDong Wu
ZiHan Li
ZhenLi Si
spellingShingle HaiDong Wu
ZiHan Li
ZhenLi Si
Trajectory tracking control for four-wheel independent drive intelligent vehicle based on model predictive control and sliding mode control
Advances in Mechanical Engineering
author_facet HaiDong Wu
ZiHan Li
ZhenLi Si
author_sort HaiDong Wu
title Trajectory tracking control for four-wheel independent drive intelligent vehicle based on model predictive control and sliding mode control
title_short Trajectory tracking control for four-wheel independent drive intelligent vehicle based on model predictive control and sliding mode control
title_full Trajectory tracking control for four-wheel independent drive intelligent vehicle based on model predictive control and sliding mode control
title_fullStr Trajectory tracking control for four-wheel independent drive intelligent vehicle based on model predictive control and sliding mode control
title_full_unstemmed Trajectory tracking control for four-wheel independent drive intelligent vehicle based on model predictive control and sliding mode control
title_sort trajectory tracking control for four-wheel independent drive intelligent vehicle based on model predictive control and sliding mode control
publisher SAGE Publishing
series Advances in Mechanical Engineering
issn 1687-8140
publishDate 2021-09-01
description For four-wheel independent drive intelligent vehicle, the longitudinal and lateral motion control of the vehicle is decoupled and a hierarchical controller is designed: the upper layer is the motion controller, and the lower layer is the control distributor. In the motion controller, the model predictive control (MPC) is used to calculate the steering wheel angle and the total yaw moment for lateral control, and the sliding mode control (SMC) is used to calculate the total driving force for longitudinal control. In order to improve the control algorithm adaptability and the tracking accuracy at high speed, the UniTire model that can accurately express the complex coupling characteristics of tire under different working conditions are used and the numerical partial derivative of the state equation is used in MPC controller to ensure the feasibility of the algorithm. The control distributor distributes the total yaw moment and driving force calculated by the motion controller of the four wheels through the objective optimization function, and the constraints on road adhesion condition and the constraints on actuators are considered at the same time. A co-simulation platform is built in the CarSim/Simulink environment and the MPC-SMC controller is compared with the previously established MPC controller.
url https://doi.org/10.1177/16878140211045142
work_keys_str_mv AT haidongwu trajectorytrackingcontrolforfourwheelindependentdriveintelligentvehiclebasedonmodelpredictivecontrolandslidingmodecontrol
AT zihanli trajectorytrackingcontrolforfourwheelindependentdriveintelligentvehiclebasedonmodelpredictivecontrolandslidingmodecontrol
AT zhenlisi trajectorytrackingcontrolforfourwheelindependentdriveintelligentvehiclebasedonmodelpredictivecontrolandslidingmodecontrol
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