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

鲸鱼 计算机科学 理论(学习稳定性) 跟踪(教育) 路径(计算) 优化算法 电子稳定控制 控制(管理) 控制理论(社会学) 算法 人工智能 数学优化 航空航天工程 工程类 数学 机器学习 渔业 程序设计语言 生物 教育学 心理学
作者
Chuang Zhang,Yong Zhang,Fengkui Zhao,Yanbin Qin
出处
期刊:Physica Scripta [IOP Publishing]
卷期号:100 (6): 065216-065216 被引量:3
标识
DOI:10.1088/1402-4896/add05d
摘要

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.
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