Development and Validation of a Linear Motor-Based Active Suspension System Using Advanced Control Techniques

This paper aims to enhance the performance of automotive suspension systems by designing, modelling, and experimentally implementing an active suspension system based on a linear motor actuator. The study begins with the development of a simulation model for a passive suspension system, which is then validated against experimental data collected from a custom-built physical test rig. Following validation, the system is upgraded to an active configuration where four control strategies are examined: Proportional-Integral-Derivative (PID), Fuzzy-tuned PID (FPID), Sliding Mode Control (SMC), and Model Predictive Control (MPC). Each controller is evaluated based on its ability to minimize sprung mass displacement and improve ride comfort under excitation conditions. The advantages and limitations of each method are discussed in detail. Simulation and experimental results reveal that active control significantly outperforms passive suspension, particularly at low-frequency excitations, where real-world tests showed up to 89% reduction in vertical displacement. These findings demonstrate the practical feasibility and effectiveness of linear-motor-based active suspension systems for automotive applications.