Artificial intelligent technique applied to semi-active vibration control of vehicle suspension system

The study investigates to quantify the benefits of magnetorheological (MR) dampers in enhancing ride comfort, vehicle stability, and overall system performance in semi-active suspension systems. Magnetorheological (MR) dampers in semi-active suspension systems work together with active and passive suspension technologies to make them more effective and flexible. The study investigates to quantify the benefits of magnetorheological (MR) dampers in enhancing ride comfort, vehicle stability, and overall system performance in semi-active suspension systems. Magnetorheological (MR) dampers in semi-active suspension systems work together with active and passive suspension technologies to make them more effective and flexible. The complete dynamic system model encompasses essential performance parameters such as seat travel, body acceleration, passenger acceleration, suspension travel, and tire deflection. This research reveals that the suggested artificial intelligence, such as a variable structure fuzzy proproportional-integral-derivative (VSC-FPID) controller, substantially enhances these performance indicators when exposed to varied road profiles. In engineering systems, the control performance criteria will be evaluated in both the time and frequency domains. The performance of the proposed controller is examined by simulation of a quarter-car model with three degrees of freedom (3 DOF) using MATLAB/Simulink software. When compared to passive suspension systems, PID control techniques, and fuzzy PID control strategies, analysis of the simulated initial findings found that the improved VSC-FPID controller significantly improves ride comfort and vehicle stability.