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.
Highlights
In recent years, unmanned vehicles have become a research hotspot due to the increase of various traffic problems such as traffic congestion and traffic accidents [1]
The Pure Pursuit based on the symmetrical front and the rear wheels steering (SFRWS) (PP-SFRWS) model tracking method, the Model Predict Control based on the SFRWS (MPC-SFRWS) model, and the Model Predict Control based on the model unconstrained the front and the rear wheels steering (MPC-UFRWS) are compared and verified
A path tracking controller with unconstrained front and rear wheels steering is established for the trajectory tracking control of 4WS vehicle
Summary
In recent years, unmanned vehicles have become a research hotspot due to the increase of various traffic problems such as traffic congestion and traffic accidents [1]. Fnadi et al [21] synthesized a new controller for dynamic path tracking by using constrained model predictive control (MPC) for double steering off-road vehicles, which takes into account steering and sliding constraints to ensure safety and lateral stability These methods only use rear-wheel steering within a small turning angle range and are not suitable for flexible control of 4WS vehicle at low speed. Due to the constraint between the front and rear wheel angle relationship, the SFRWS model limits the steering freedom of 4WS vehicle, which reduces flexibility For this reason, this paper proposes a predictive control method based on the unconstrained steering model of 4WS.
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