Active force control with iterative learning control algorithm applied to vehicle suspension system

Abstract

The paper introduces a new control method to a passenger vehicle active suspension system using Active Force Control (AFC) integrated with Iterative Learning Control (ILC) algorithm and the classic proportional-integral-derivative (PID) control known as the AFCIL control scheme. The overall control system consists of three feedback control loops, namely, the innermost loop for the force tracking of the pneumatic actuator using proportional-integral (PI) controller, the intermediate loops applying AFC with iterative learning algorithm for the compensation of the disturbances, and the outermost loop using PID controller for the computation of the desired force. A study is carried out both via simulation and experimental approaches. The simulation was done using MATLAB/Simulink software with Control System Toolbox (CST) and the experiment was carried out on a physical quarter car test rig with hardware-in-the-loop simulation (HILS) feature that fully incorporates the underlying theoretical elements. The performance of the AFCIL scheme was evaluated and compared with the pure PID controller and passive counterpart to examine the effectiveness of the system in suppressing the vibration effect of the suspension system that may improve the riding comfort performance. Both simulation and experimental results show that the AFCIL scheme is much superior compared to the PID and passive counterparts.