Parameter Optimization Study of Bionic Semi-Active Air Suspension Control System Applied to Adaptive Fuzzy PID

Abstract

The semi-active air suspension system is first built in this paper based on the characteristics of air springs, and the semi-active air suspension system is then bionic controlled by introducing a nonlinear bionic reference model to build a two-degree-of-freedom 1/4 bionic semi-active air suspension vehicle model. The fundamental idea of adaptive fuzzy PID control is then shown using the PID controller's control law, and the fuzzy control rule table is created by choosing the appropriate PID controller settings. Finally, the joint modeling of the vehicle model was carried out using ADAMS and MATLAB, and the smoothness of the vehicle driving was analyzed. The findings demonstrate that, compared to passively controlled vehicles on the three ABC routes, the bionic semi-active air suspension control system optimized by adaptive fuzzy PID control increases vehicle mass acceleration by 40.29%, 42.02%, and 40.84%, respectively. This demonstrates yet another way that the vehicle's air suspension performance and stability may be further enhanced by parameter optimizing the bionic semi-active air suspension control system using adaptive fuzzy PID control.