Optimal Control Method of Path Tracking for Four-Wheel Steering Vehicles

Abstract

Path tracking is a key technique for intelligent electric vehicles, while four-wheel steering (4WS) technology is of great significance to improve its accuracy and flexibility. However, the control methods commonly used in path tracking for a 4WS vehicle cannot take full advantage of the additional steering freedom of the 4WS vehicle, because of restricting the relationship between the front and rear wheels steering angle. To address this issue, we derive a kinematic model without the restriction based on the small-angle assumption. Then, the objective function and constraints of system control quantity optimization are designed based on the tracking error model. After the optimization problem is solved in the form of quadratic programming with constraints, the control sequence with the smallest performance index is obtained through rolling optimization. The proposed method is tested on a high-fidelity Carsim/Simulink co-simulation platform and an experimental vehicle. The results show that the standard deviation of the lateral error and the yaw angle error of the algorithm is less than 0.1 m and 3.0°, respectively. Compared with the other two algorithms, the control of the front and rear wheels angle of this method is more flexible and the tracking accuracy is higher.

Path Tracking Control With Four-Wheel Independent Steering, Driving and Braking Systems for Autonomous Electric Vehicles

“…This fact is common to the other driver models such as Stanley method and PID control [31]. The error dynamics based path tracking controller can be used for a vehicle with 4WS because the front and rear steering angles are explicitly expressed as a control input of the controllers such as LQR and MPC [33][34][35][36][37][38][39][40]. However, in this case, assumptions on a target path are required to build the error dynamics.…”

“…Typical driver model for path tracking control is pure pursuit and Stanley methods. Another method is to use an error dynamics on a target path and to apply optimal control methodologies or sliding mode control with it for controller design [33][34][35][36][37][38][39][40]. In the method, the errors of the lateral offset and heading are used to define the plant model for controller design.…”

“…Recent advances in path tracking control were summarized in the literature [27][28][29][30][31][32]. Among them, the path tracking control was investigated for a vehicle with 4WS or 4WD [4,9,16,[33][34][35][36][37][38][39][40]. The recent studies on the path tracking control with 4WS and 4WD are summarized in Table I.…”

Internet of Robotic Things (IoRT) and Metaheuristic Optimization Techniques Applied for Wheel-Legged Robot

“…The robot was equipped with two turnable wheels at the front axle. This allowed calculation of the control kinematics according to the car-like Ackermann model [54]. Figure 13 presents the vectors of the steering process in accordance with the dynamic turning point, O.…”

Integrated Path Tracking and Lateral Stability Control with Four-Wheel Independent Steering for Autonomous Electric Vehicles on Low Friction Roads

“…Generally, most path tracking controllers have been designed for a front wheel steering (FWS) vehicle. By virtue of recent advances in actuators for VSC in EV-IWM, 4WS, 4WIS and 4WID have been widely adopted for path tracking control [24][25][26][27][28][29][30][31][32][33][34][35][36][37][38][39][40][41]. Among them, a lot of papers have been published on the path tracking control for a vehicle with 4WS and/or 4WD [24,[26][27][28][29][32][33][34]38,41].…”