Research on path tracking of intelligent vehicle based on optimal deviation control

ABSTRACT

Aiming at the problem that the transformer substation intelligent detection of vehicles in the process of moving away from the planning path, based on the four-wheel model vehicle, this paper proposes a fuzzy adaptive PID path tracking control method based on optimal lateral deviation. Firstly, the kinematic model and the equation of the linear 2-DOF of the vehicle are established by taking the front wheel steering angle of the model vehicle as the input of the control system. Secondly, the linear quadratic regulator (LQR) is introduced to minimize the transverse tracking error between the model vehicle and the expected path. Finally, the control parameters of the fuzzy PID are updated with the lateral deviation and the variation rate of the deviation, and the front wheel steering angle of the Vehicle is adjusted adaptively to realize the stable tracking of the desired path. The simulation results show that the tracking error of the proposed path tracking control method is concentrated between -0.08m and +0.08m, and the desired path can be better tracked.

KEYWORDS:

• Optimal deviation control
• intelligent vehicle
• fuzzy adaptive controller
• LQR
• desired path
• path tracking

Funding

This work was financially supported by Electric Power Research Foundation funded project (2017KF28).

Additional information

Funding

Electric Power Research Foundation [2017KF28].