%A Liu,Xinhua %A Wang,Ningning %A Wang,Kun %A Huang,Hui %A Li,Zhixiong %A Sarkodie-Gyan,Thompson %A Li,Weihua %D 2019 %J Frontiers in Materials %C %F %G English %K Magnetorheological Damper,Semi-active seat suspension,vibration control,artificial intelligence,PID controller %Q %R 10.3389/fmats.2019.00269 %W %L %M %P %7 %8 2019-November-15 %9 Original Research %# %! Control of MRD suspension seat %* %< %T Optimizing Vibration Attenuation Performance of a Magnetorheological Damper-Based Semi-active Seat Suspension Using Artificial Intelligence %U https://www.frontiersin.org/articles/10.3389/fmats.2019.00269 %V 6 %0 JOURNAL ARTICLE %@ 2296-8016 %X This paper aims to improve control performance for a magnetorheological damper (MRD)-based semi-active seat suspension system. The vibration of the suspension is isolated by controlling the stiffness of the MRD using a proportion integration differentiation (PID) controller. A new intelligent method for optimizing the PID parameters is proposed in this work. This new method appropriately incorporates particle swarm optimization (PSO) into the PID-parameter searching processing of an improved fruit fly optimization algorithm (IFOA). Thus, the PSO-IFOA method possesses better optimization ability than IFOA and is able to find a globally optimal PID-parameter set. The performance of the PID controller optimized by the proposed PSO-IFOA for attenuating the vibration of the MRD suspension was evaluated using a numerical model and an experimental platform. The results of both simulation and experimental analysis demonstrate that the proposed PSO-IFOA is able to optimize the PID parameters for controlling the MRD semi-active seat suspension. The control performance of the PSO-IFOA-based PID is superior to that of individual PSO-, FOA-, or IFOA-based methods.