Trajectory tracking control for four-wheel independent drive intelligent vehicle based on model predictive control and sliding mode control

For four-wheel independent drive intelligent vehicle, the longitudinal and lateral motion control of the vehicle is decoupled and a hierarchical controller is designed: the upper layer is the motion controller, and the lower layer is the control distributor. In the motion controller, the model predictive control (MPC) is used to calculate the steering wheel angle and the total yaw moment for lateral control, and the sliding mode control (SMC) is used to calculate the total driving force for longitudinal control. In order to improve the control algorithm adaptability and the tracking accuracy at high speed, the UniTire model that can accurately express the complex coupling characteristics of tire under different working conditions are used and the numerical partial derivative of the state equation is used in MPC controller to ensure the feasibility of the algorithm. The control distributor distributes the total yaw moment and driving force calculated by the motion controller of the four wheels through the objective optimization function, and the constraints on road adhesion condition and the constraints on actuators are considered at the same time. A co-simulation platform is built in the CarSim/Simulink environment and the MPC-SMC controller is compared with the previously established MPC controller.

Automated summary

This study investigates the longitudinal and lateral motion control of a four-wheel independent drive intelligent vehicle and designs a hierarchical controller, with MPC and SMC algorithms for control on the upper layer and a control distributor on the lower layer. By using the UniTire model and numerical partial derivatives, the adaptability and tracking accuracy of the control algorithms are improved, considering road conditions and actuator constraints. Experimental comparisons were conducted on a co-simulation platform in the CarSim/Simulink environment.