Abstract
For distributed drive autonomous vehicles, adding lateral stability control (LSC) to the trajectory tracking control (TTC) can optimize the distribution of the driving torque of each wheel, so that the vehicle can track the planned trajectory while maintaining stable lateral motion. However, the influence of adding LSC on the TTC system is still unclear. Firstly, a stability-track hierarchical control structure composed of LSC and TTC was established, and the interaction between the two layers was identified as the key of this paper. Then, the Intrinsic Mechanistic framework of the stability-tracking control (STC) was proposed by establishing and analyzing the vehicle dynamic model and control process of two layers. Finally, through simulation experiments, it was found that the change in the curvature of the target trajectory will make the tracking target trajectory and maintaining the lateral stability of the vehicle appear to conflict; in addition, in the LSC layer, the steering characteristics and delay characteristics of different reference models have a greater impact on the lateral stability and trajectory tracking performance; moreover, adjusting the preview time has a more obvious effect on trajectory tracking and lateral stability than the stability correction intensity coefficient.
Highlights
IntroductionPublisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations
Comparing the control logic of the lateral stability control (LSC) layer with that of the trajectory tracking control (TTC) layer, it can be found that the former exerts its effect on the latter in two ways: one is through the front wheel steer angle and the braking/driving force directly affect the calculation of reference yaw rate and additional yaw moment, the second is through the state feedback from the vehicle dynamics coupling motion indirectly
In order to investigate the intrinsic mechanism of stability-tracking control and to obtain the best control results, this paper quantitatively and qualitatively investigates the effects of parameters, two control objectives and reference models on the STC system by designing simulation experiments
Summary
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. A large number of trajectory tracking algorithms have been applied to autonomous motion control subsystems, such as Stanley Model, Optimal Preview Control (OCM), Proportion Integration Differentiation (PID), Model predictive control (MPC), linear quadratic regulator (LQR), Sliding Mode Control (SMC), H∞ control, Neural Network Model (NNM), etc., [11,12] These algorithms only provide the vehicle with the ability to perform direction and speed control under good road adhesion conditions, but they seldom consider the lateral stability under extreme conditions. The intrinsic mechanism of STC is not clear Research on this issue has the following significance: (1) by analyzing whether the TTC and LSC will conflict under their respective control objectives, guidance can be put forward for the stability-tracking coordination control method; (2) and by analyzing the process of STC, the main factors affecting STC can be found, and the efficiency of the STC system can be improved.
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