Research on 4WS Agricultural Machine Path Tracking Algorithm Based on Fuzzy Control Pure Tracking Model

This paper presents a path tracking algorithm based on a fuzzy control pure tracking model for autonomous navigation of 4WS agricultural machines. The aim of this research is to implement path tracking for unmanned 4WS agricultural machinery and to solve the problem of difficult determination of forward-looking distances in pure tracking algorithms. By using the pure tracking algorithm model and a fuzzy controller, this paper converts the heading deviation and lateral deviation in one control cycle into the sum of lateral deviation as the first input to the fuzzy controller and the vehicle travel speed as the second input to the fuzzy controller, thus outputting the actual forward-looking distance. In order to verify the practicality, accuracy, and path tracking precision of the proposed path tracking algorithm, a straight-line path tracking test under variable speed conditions and a turning path tracking test under non-fixed forward-looking distance conditions were carried out using a test platform after simulation on MATLAB/Simulink in this paper. The test results show that: in the straight-line path tracking process, the maximum overshoot is 0.123 m, and after stable driving, the maximum lateral deviation of the straight-line tracking part is 0.058 m and the steady-state deviation is 0.039 m; in the bow-turn path tracking process, the absolute value of the maximum lateral deviation of the actual driving trajectory of the farm machine from the desired path is 0.139 m, and the average tracking deviation is 0.041 m. It can be seen that the path tracking control algorithm proposed in this paper has good tracking accuracy as well as convergence, and can meet the demand for the autonomous navigation function of 4WS agricultural machinery, which has a certain application value.