Figure 2.PID feed-forward control
2.2 PP algorithm
PP algorithm is a more reliable path tracking control algorithm, Figure
3 shows the geometric relationship schematic diagram of PP algorithm,
its principle is to control the vehicle turning radius R, so that the
vehicle rear axle center point along the arc to reach the reference path
target point (gx, gy) with forward-looking distance l, and then based on
Ackermann steering model to calculate the required front wheel turning
angle δ for control [29]. This control method has simple control and
better robustness, even if large lateral errors and curvature changes
occur in the tracking process still achieve better tracking results
[30].
Previous studies have shown that the PP-based algorithm or the improved
PP algorithm can effectively achieve path tracking under low-speed
conditions. For example, literature [31] designed a path tracking
controller based on PP algorithm, verified the effectiveness of the
controller in tracking under low-speed conditions, and proved that the
algorithm leads to complete loss of vehicle stability under high-speed
conditions.Yang et al. proposed an improved PP tracking algorithm based
on the optimal target point based on the problem of forward distance
calculation, which finds the optimal target point by simulating the
driver’s forward behavior, and compared with traditional PP algorithm,
the tracking error is reduced by more than 20% [32].
The PP algorithm or the improved PP algorithm also has more applications
in the path tracking control of parking and farm scenarios. For example,
Yu et al. implemented path tracking in a parking scenario based on the
PP algorithm, and the results showed that the algorithm met the
requirements of smoothness, ride comfort, and safety through the
continuous transformation of the steering wheel angle [33].Zhang et
al. designed a path tracking algorithm for autonomous navigation of
agricultural machines using PP and fuzzy control algorithms [34],
and Wang et al. designed a PP model for agricultural applications by
adding the heading error rate PP model for agricultural applications,
and both showed good tracking accuracy and convergence of the improved
algorithm through testing [35].
However, the tracking performance of the PP algorithm depends on the
choice of the forward-looking distance, which is difficult to obtain the
optimal value, and the tracking performance deteriorates due to the
large difference between the system model and the actual vehicle
characteristics under high-speed conditions, so the PP algorithm is
generally suitable for path tracking control under low speed and small
lateral acceleration.