Path tracking of autonomous tractor based on model-free adaptive control

Abstract

Autonomous tractors, with path tracking as one of the key technologies, have become a research hotspot in recent years. However, the nonlinearity of and uncertainties in the autonomous tractor path tracking process can lead to challenges in terms of control. Although the model-based control method has been widely used in path tracking and achieved good results, only a limited number of model-free adaptive control (MFAC) methods have been developed for path tracking. This paper proposes an MFAC path tracking controller for autonomous tractors based on the use of a preview heading deviation method in which the preview heading angle is used as an input to control the steering, enabling the controller to achieve a small lateral error and stable control. In the simulation, the tracking effects of the designed controller, proportional integral differential (PID) and pure pursuit controllers at different speeds were compared. The results show that the proposed controller has good tracking ability and adaptability and can achieve high tracking accuracy. Finally, the tracking errors of the designed and PID controllers were compared in a real vehicle test, with the results verifying the effectiveness and practicality of the designed controller.