Robust hierarchical control for LPV systems of CDC semi-active suspensions

The suspension system is an important component of the vehicle, with the development of controllable suspension, the performance requirements of the vehicle suspension system are getting higher and higher. Usually, the suspension system is simplified as a linear system in the full vehicle control, but the actual continuous damping control (CDC) semi-active suspension force will be nonlinear with the motion of the damper. In addition, the control performance is also affected by the accuracy of the actual actuator output force. In this paper, a hierarchical control method for a CDC semi-active suspension linear parameter varying (LPV) system is designed. The nonlinear LPV model of CDC semi-active suspension is established, based on which the upper-level robust LPV- H ∞ control strategy is designed. A dataset is established based on damping characteristics experiments, and a lower-level force tracking predictive control strategy is designed using cubic spline interpolation and a random forest model improved with Bayesian optimization. Simulation results show that the designed hierarchical control method can accurately realize the tracking prediction of the damping force and effectively improve the ride comfort of the full vehicle. And the full vehicle test platform is further built for road tests to evaluate the system performance. The results under randomized road conditions show that the root mean square values of the full vehicle vertical, pitch, and roll acceleration are reduced by 41.38%, 32.11%, and 31.27%, respectively, compared with the passive suspension. The method better improves the full vehicle performance.