A Path Following Lateral Control Scheme for Four-Wheel Independent Drive Autonomous Vehicle Using Sliding Mode Prediction Control

Wang, Weida; Ma, Taiheng; Chao, Yang; Zhang, Yuhang; Liu, Ying; Qie, Tianqi

doi:10.1109/tte.2022.3170059

Cited by 25 publications

(12 citation statements)

References 31 publications

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“…The vehicle dynamics model established in this paper is designed to both accurately describe the vehicle dynamics and to simplify them as much as possible. Therefore, the following assumptions are made for the vehicle dynamics model [9]: 1) the pitch, roll and vertical motion of the vehicle is ignored; 2) the effect of the steering system is neglected, the target vehicle adopts front wheel steering and the coaxial wheels have the same steering angle; 3) the lateral load transfer of the tyres is not considered.…”

Section: Dof Vehicle Dynamics Modelmentioning

confidence: 99%

A study on integrated control of trajectory tracking and lateral stability for distributed drive autonomous vehicle

Shi,

Yin

2023

International Conference on Automation Control, Algorithm, and Intelligent Bionics (ACAIB 2023)

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In this paper, an integrated control strategy integrating trajectory tracking and lateral stability is proposed for a distributed drive autonomous vehicle (DDAV). First, a model prediction controller is established based on a 3 degree-of-freedom (DOF) vehicle dynamics model and a path following model, and the optimal front wheel steering angle and external yaw moment are simultaneously obtained. Then the torque distribution controller optimises the distribution of longitudinal forces at each wheel with the tyre load rate minimisation as the objective function, and applies the interior point method to solve the optimal torque distribution problem. Finally, simulation experiments are carried out based on the Carsim-Simulink joint simulation platform. The results show that the proposed integrated control strategy can effectively control the lateral error and heading error in vehicle trajectory tracking, and ensure reliable lateral stability of the vehicle at the same time.

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Section: Dof Vehicle Dynamics Modelmentioning

confidence: 99%

A study on integrated control of trajectory tracking and lateral stability for distributed drive autonomous vehicle

Shi,

Yin

2023

International Conference on Automation Control, Algorithm, and Intelligent Bionics (ACAIB 2023)

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“…where 𝛼 i is the relaxation time constant, F yi is the lateral tire force obtained from linear tire model (4). Using (4), (5), and (9), the front and rear tires lateral dynamic force models are obtained as follows:…”

Section: Estimation Of Tire Cornering Stiffnessmentioning

confidence: 99%

“…The lateral motion control of IWMD‐EV is more effective in enhancing vehicle safety and preventing accidents [4, 5]. In literature, various control methods have been developed for lateral motion control addressing actuator faults and external perturbations in vehicle modelling [6, 7].…”

Section: Introductionmentioning

confidence: 99%

Novel reaching law based predictive sliding mode control for lateral motion control of in‐wheel motor drive electric vehicle with delay estimation

Chiliveri,

Kalpana,

Subramaniam

et al. 2023

IET Intelligent Trans Sys

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The lateral motion control of an in‐wheel motor drive electric vehicle (IWMD‐EV) necessitates an accurate measurement of the vehicle states. However, these measured states are always affected by delays due to sensor measurements, communication latencies, and computation time, which results in the degradation of the controller performance. Motivated by this issue, a novel reaching law based predictive sliding mode control (NRL‐PSMC) is proposed to maintain the lateral motion control of the IWMD‐EV subjected to unknown time delay. Initially, a PSMC framework is built, in which a predictor integrating with the sliding mode control is designed to eliminate the effect of time delay and generate the virtual control signals. Further, to alleviate the chattering phenomenon, a novel‐reaching law is developed, enabling the vehicle to track the desired states effectively. Subsequently, a dynamic control allocation technique is presented to optimally allocate the virtual control input to the actual control input. The accurate estimation of the aforementioned unknown delay is realized through a delay estimator. Finally, simulation and hardware‐in‐the‐loop experiments are performed for three specific driving manoeuvres, and the results demonstrate the effectiveness of the proposed controller design.

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“…Through the analysis and summary of previous research results, we found that during the path following process, a vehicle's stability was becoming more and more important compared with the accuracy of the path following process in recent literatures. In Wang et al, 20 a torque distribution method based on tire force observations ensured the driving stability of 4WID. By combining two sliding mode surface approaches, Xie et al 16 took into account the vehicle stability during path following process.…”

Section: Introductionmentioning

confidence: 99%

Path following control for 4WID-EV based on extended state observer and sliding mode control considering yaw stability

Wang

Xia

2023

Advances in Mechanical Engineering

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Automatic driving technology has developed over time and the path-following problem for four-wheel independent drive electric autonomous vehicles (4WID-EV) is a topic of increasing interest. During the path-following process, a consideration of uncertainties in vehicle modeling including parameter variation, modeling error, and external disturbances is made, which have an important effect on path-tracking performance. As so, we proposed a new path following control strategy that can be applied to robotics applications. First, it was determined to establish a 2 DOF dynamic model and path following error model, and were then converted to yaw angle tracking problems. Therefore, the desired control input of steering angle was obtained via yaw angle tracking controller. To estimate and compensate the uncertainties associated with systems, the nonlinear extended state observer (NESO) was designed while the NTSM controller was used to realize yaw angle tracking. Next, considering the system stability, a sliding mode controller with modified reaching law was used to obtain the desired additional yaw moment. Then, the optimized torque distributor was designed for allocating optimal tire forces. Finally, the simulation experiments were carried out in Matlab/Simulink and Carsim joint simulation platform. In conclusion, the proposed control scheme exhibits highly accurate path following as well as strong robustness to speed, tire-road friction coefficient and external disturbance.

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A Path Following Lateral Control Scheme for Four-Wheel Independent Drive Autonomous Vehicle Using Sliding Mode Prediction Control

Cited by 25 publications

References 31 publications

A study on integrated control of trajectory tracking and lateral stability for distributed drive autonomous vehicle

A study on integrated control of trajectory tracking and lateral stability for distributed drive autonomous vehicle

Novel reaching law based predictive sliding mode control for lateral motion control of in‐wheel motor drive electric vehicle with delay estimation

Path following control for 4WID-EV based on extended state observer and sliding mode control considering yaw stability

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