Experimental evaluation of ride comfort performance for suspension system using PID and fuzzy logic controllers by advanced firefly algorithm

Control systems based on fuzzy logic (FL) and proportional–integral–derivative (PID) are among the effective controllers which operate using an inference mechanism rule base and control loop mechanism that continuously calculates an error value. Because of that both of them are being used as a practical solution for major vibration problems in many applications recently. However, in automotive suspension applications, the number of study on reducing the amplitude vibration of vehicle ride comfort using these controllers, especially in the experimental study, is still limited. Thus, this study aims to improve the performance of the said controllers by integrating with a modified version of the algorithm known as the advanced firefly algorithm (AFA) in the suspension system application. An experimental quarter vehicle test rig complete with a magnetorheological (MR) damper is used in this study to test and compare the effectiveness of the proposed FL-AFA and PID-AFA controllers against the passive controller system. An external disturbance in the form of sinusoidal waves is applied to the system to verify the sensitivity and durability of the proposed control schemes, and consequently, a comparative study is performed to analyze the system characteristics. Two major issues known as the disturbance rejection and damping constraint are investigated and overcome by proposing a good controller scheme with intelligent optimizers. The experiment result indicates that the PID-AFA shows a good response compared to the FL-AFA and the passive system, with the ability to reduce the vibration amplitude by up to 57.1%.