Research on 4WIS-4WID intelligent vehicle path tracking and stability cooperative control strategy based on improved whale optimization algorithm

Abstract The independently controllable wheels of a 4WIS/4WID vehicle endow it with high maneuverability and driving stability. However, the excessive number of control inputs for wheel steering angles and motor torques significantly increases control complexity, making it challenging to balance driving stability and path-tracking accuracy. To address this issue, this paper proposes a hierarchical control strategy based on an improved Whale Optimization Algorithm (IWOA), consisting of three layers: path-tracking, stability control, and torque-angle allocation. First, a front-wheel steering controller is designed based on a single-point preview deviation model to achieve path-tracking control. Second, a sliding mode controller integrating rear-wheel steering and direct yaw moment control is developed based on a two-degree-of-freedom vehicle model and sliding mode control theory. This controller mitigates the adverse effects of sideslip angle deviation and yaw rate deviation on vehicle stability. A novel reaching law is introduced to suppress chattering in the sliding mode controller. Additionally, dynamic load transfer and Ackermann steering theory are employed to distribute wheel torques and steering angles, respectively. Finally, to address the issue of control coupling between wheel steering angles and drive torques caused by the difficulty of multi-parameter tuning in the sliding mode controller, an improved Whale Optimization Algorithm (IWOA) is proposed. The enhancement incorporates three strategies: chaotic mapping-based initialization, nonlinear convergence factor updating, and adaptive inertia weight adjustment. Furthermore, a comprehensive fitness function that considers both vehicle stability and path tracking accuracy is designed, and the proposed algorithm is applied to optimize the parameters of the sliding mode controller. Simulation results demonstrate that, compared to front-wheel steering and 4WIS-4WID control strategies, the proposed 4WIS-4WID intelligent vehicle control strategy based on IWOA achieves the best performance, significantly enhancing driving stability while ensuring high path-tracking accuracy.

Authors

Institutions

Publication Details

Journal
Physica Scripta
Published
2025-04-24
DOI
https://doi.org/10.1088/1402-4896/add05d
Citations
1
Primary Topic
Advanced Algorithms and Applications
Type
article
Field-Weighted Citation Impact
1.21
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Research on 4WIS-4WID intelligent vehicle path tracking and stability cooperative control strategy based on improved whale optimization algorithm

Fengkui Zhao, Chuang Zhang, Yong Zhang, Yanbin Qin
1 citations
Physica Scripta
Advanced Algorithms and Applications
1.21
article

Research on 4WIS-4WID intelligent vehicle path tracking and stability cooperative control strategy based on improved whale optimization algorithm

Fengkui Zhao, Chuang Zhang, Yong Zhang, Yanbin Qin
article en
1 citations

Abstract

Abstract The independently controllable wheels of a 4WIS/4WID vehicle endow it with high maneuverability and driving stability. However, the excessive number of control inputs for wheel steering angles and motor torques significantly increases control complexity, making it challenging to balance driving stability and path-tracking accuracy. To address this issue, this paper proposes a hierarchical control strategy based on an improved Whale Optimization Algorithm (IWOA), consisting of three layers: path-tracking, stability control, and torque-angle allocation. First, a front-wheel steering controller is designed based on a single-point preview deviation model to achieve path-tracking control. Second, a sliding mode controller integrating rear-wheel steering and direct yaw moment control is developed based on a two-degree-of-freedom vehicle model and sliding mode control theory. This controller mitigates the adverse effects of sideslip angle deviation and yaw rate deviation on vehicle stability. A novel reaching law is introduced to suppress chattering in the sliding mode controller. Additionally, dynamic load transfer and Ackermann steering theory are employed to distribute wheel torques and steering angles, respectively. Finally, to address the issue of control coupling between wheel steering angles and drive torques caused by the difficulty of multi-parameter tuning in the sliding mode controller, an improved Whale Optimization Algorithm (IWOA) is proposed. The enhancement incorporates three strategies: chaotic mapping-based initialization, nonlinear convergence factor updating, and adaptive inertia weight adjustment. Furthermore, a comprehensive fitness function that considers both vehicle stability and path tracking accuracy is designed, and the proposed algorithm is applied to optimize the parameters of the sliding mode controller. Simulation results demonstrate that, compared to front-wheel steering and 4WIS-4WID control strategies, the proposed 4WIS-4WID intelligent vehicle control strategy based on IWOA achieves the best performance, significantly enhancing driving stability while ensuring high path-tracking accuracy.

Physica ScriptaVol. 100(6)
Nanjing Forestry University (CN), Xuzhou Construction Machinery Group (China) (CN)
Openalex Percentile: Top 22%
Advanced Algorithms and Applications
1.21
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.