APPLIED SCIENCES, cilt.13, sa.20, ss.1-23, 2023 (SCI-Expanded)
Featured Application An implementation of PID controller optimized with PSO to improve the road holding and ride comfort simultaneously on a real suspension test setup was proposed. The manuscript contains valuable experimental results for suspension system controller researchers.Abstract This study presents an implementation of a proportional-integral-derivative (PID) controller utilizing particle swarm optimization (PSO) to enhance the compromise on road holding and ride comfort of a quarter car semi-active suspension system (SASS) through simulation and experimental study. The proposed controller is verified with a processor-in-the-loop (PIL) approach before real-time suspension tests. Using experimental data, the magnetorheological damper (MR) is modeled by an artificial neural network (ANN). A series of experiments are applied to the system for three distinct bump disturbances. The algorithm performance is evaluated by various key metrics, such as suspension deflection, sprung mass displacement, and sprung mass acceleration for simulation. The phase plane method is used to prove the stability of the system. The experimental results reveal that the proposed controller for the SASS significantly improves road holding and ride comfort simultaneously.