Predictive control method for the path tracking of agricultural machinery based on preview model

A path tracking system is required to fully meet the change of operating speed in the agricultural machinery. In this study, a predictive control system was proposed using a preview kinematics model. The model of preview heading error was also established using the preview following theory. The output equation was combined with the conventional state equation of path tracking error. The state space model of path tracking error was then constructed for the preview kinematic after linearization and discretization. Then the path tracking control was designed using a model predictive control algorithm and input parameterized attenuation. The co-simulation platform was built for the path-tracking control of agricultural machinery using CarSim and Simulink software. The simulation results showed that the lateral errors of straight path tracking asymptotically approached zero for the preview model predictive controller. There was no overshoot of driving curves at different operating speeds. Once the operating speeds of agricultural machinery were 1, 3 and 5 m/s, respectively, the maximum absolute values of lateral error were 8.52, 10.42, and 10.82 cm in the circular path tracking for the preview model predictive controller, whereas, the standard values of lateral error were 3.96, 5.83 and 6.17 cm, respectively. Once the control horizon layers were 10, 30 and 60, the operation period of the preview model predictive controller was reduced by 7.5%, 43.0% and 48.5%, respectively, compared with the conventional. The preview model predictive controller was used to dynamically adjust the preview distance and prediction horizon, according to the operating speed and path curvature, respectively. The dynamic performance of the path tracking system was effectively improved with the control accuracy. There was more balanced path tracking at different operating speeds, indicating the simpler parameter setting. The decay factor was also introduced to parameterize the control input. The amount of online optimization was greatly reduced to improve the real-time performance of path-tracking control. The field test platform of automatic driving was built to install the satellite antenna, satellite receiver, angle sensor, proportional reversing valve, controller, and vehicle touch screen on the agricultural machinery. In straight path tracking, the average maximum absolute values of lateral error were 3.50 and 5.32 cm, the average absolute values of lateral error were 1.46 and 1.93 cm, and the average standard values of lateral error were 1.71 and 2.38 cm, respectively, when the operating speeds of agricultural machinery were 1 and 5 m/s, respectively. In circular path tracking, the average maximum absolute values of lateral error were 9.62 and 15.34 cm, the average absolute values of lateral error were 5.17 and 7.86 cm, and the average standard values of lateral error were 4.82 and 8.39 cm, respectively, when the operating speeds of agricultural machinery were 1 and 5 m/s, respectively. The field test results showed that the preview model predictive controller shared a strong adaptability to the change of operating speed within the operating speed range of 0.5 to 5 m/s. Agricultural machinery quickly and stably tracked the reference path with high control accuracy. The average maximum absolute values and the average standard values of lateral error were less than 5.5 and 2.5 cm, respectively, for the straight path tracking, while less than 15.5 and 8.5 cm, respectively, for the circular path tracking. The preview model predictive controller can fully meet the actual control requirements of agricultural machinery, especially suitable for complex environments or high-speed conditions.