Active Suspension System for Passenger Vehicle using Active Force Control with Iterative Learning Algorithm

The paper describes the practical implementation of a new hybrid control method to a vehicle suspension system using Active Force Control (AFC) with Iterative Learning (IL) and proportional-integralderivative (PID) control strategy. The overall control system essentially comprises three feedback control loops to cater for a number of specific tasks; the innermost loop for the force tracking of the pneumatic actuator using a PI controller, the intermediate loops implementing AFC with IL algorithm strategy for the compensation of the disturbances, and the outermost loop using a PID controller for the computation of the desired force. A number of experiments were carried out on a physical quarter car test rig with hardware-in-the-loop simulation (HILS) feature that fully incorporates the theoretical elements. The performance of the proposed control method was evaluated and benchmarked to examine the effectiveness of the system in suppressing the vibration effect. It was found that the experimental results demonstrate the superiority of the active suspension system with AFCIL scheme compared to the PID and passive counterparts. The vertical body acceleration and displacements are clearly reduced, thereby implying that the ride comfort aspect of the system is improved via the proposed control scheme