In this study, we developed a dynamic model and steering controller model for an autonomous tractor and evaluated their performance. The traction force was measured using a 6-component load cell, and the rotational speed of the wheels was monitored us...
In this study, we developed a dynamic model and steering controller model for an autonomous tractor and evaluated their performance. The traction force was measured using a 6-component load cell, and the rotational speed of the wheels was monitored using proximity sensors installed on the axles. Torque sensors were employed to measure the axle torque. The PI (proportional integral) controller’s coefficients were determined using the trialerror method. The coefficient of the P varied in the range of 0.1 - 0.5 and the I coefficient was determined in 3 increments of 0.01, 0.05, and 0.1. To validate the simulation model, we conducted RMS (root mean square) comparisons between the measured data of axle torque and the simulation results. The performance of the steering controller model was evaluated by analyzing the damping ratio calculated with the first and second overshoots. The average front and rear axle torque ranged from 3.29 - 3.44 and 6.98 - 7.41 kNm, respectively. The average rotational speed of the wheel ranged from 29.21 - 30.55 rpm at the front, and from 21.46 - 21.63 rpm at the rear. The steering controller model exhibited the most stable control performance when the coefficients of P and I were set at 0.5 and 0.01, respectively. The RMS analysis of the axle torque results indicated that the left and right wheel errors were approximately 1.52% and 2.61% (at front) and 7.45% and 7.28% (at rear), respectively.