Preview-based terrain adaptive active suspension control strategy for heavy-duty trucks

This paper proposes a preview-based active suspension control method for heavy-duty trucks, where the vehicle front wheel terrain preview information is employed to improve the performance of the rear, focusing on enhancing the handling stability and vehicle smoothness. To begin with, the vehicle front wheel preview information is introduced to the half-vehicle model, and a state quantity is employed to calculate the time lag between front and rear for predicting the control input of the rear wheel. Secondly, based on the developed model, an H ∞ controller is designed with the half-vehicle model based on the current stochastic linear optimal control combined with the preview controller, which provides more stable effect than the prior controllers by merging perceived ground information. Furthermore, an established seven-degree-of-freedom vehicle suspension model is utilized for the preview-based controller to govern the kinetic behavior of the heavy-duty truck, allowing for a more thorough analysis of operation smoothness and vehicle stability. At last, the vehicle comparison simulations are carried out, which indicates that the preview-based H ∞ controller designed by inspecting the terrain preview information can straighten out the smoothness and safety of the heavy-duty truck more effectively in contrast with the LQG controller.