Optimizing Vibration Attenuation Performance of a Magnetorheological Damper-Based Semi-active Seat Suspension Using Artificial Intelligence

Abstract

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.

An Active Control with a Magnetorheological Damper for Ambient Vibration

“…A 5-DOF driver and seat suspension system model for active vibration control was established by Zhao et al [20] and a quick identification method of seat-occupant system parameters based on vibration measurement data optimized by a multi-objective Genetic Algorithm was proposed. In order to improve the attenuation performance of a semi-active seat suspension system based on magnetorheological damper, a new intelligent optimization method of PID parameters to regulate the stiffness of magnetorheological damper and actively control vibration was proposed by Liu et al [21].…”

Data-driven prediction-control system modeling for magnetorheological damping force

“…In recent years, with the advancement of algorithms and data science, some artificial intelligence control schemes based on bio-inspired fruit fly algorithm that uses a hybrid algorithm to optimize the controller are proposed and verified the method is superior to that of individual ones (Bhardawaj et al, 2020;Liu et al, 2019). Of course, a hybrid control strategy combing the data-driven method to reduce the model errors and fractional-order derivative (FD) -based sliding mode control technique was carried out (Nguyen et al, 2020(Nguyen et al, , 2021, which verified the control effectiveness as well as the possibility of development of this orientation.…”

A review on multi-physics numerical modelling in different applications of magnetorheological fluids

“…It can be seen that the transmissibility curve due to applying the Skyhook control algorithm is better than the counterparts obtained by applying either a constant or no magnetic field. Research on better performance of MR dampers due to the employment of control loops attracts more interests, as reported by Christie et al (2019) and Liu et al (2019). A rotary MR damper employed with the purpose of seismic vibration suppression was presented by Christie et al (2019).…”

“…The damper performance was tuned by a short-time Fourier transform (STFT) control algorithm. On the other hand, a proportional–integral–derivative (PID) controller was employed by Liu et al (2019) to control the performance of a linear MR damper. The performances of MR dampers due to the employment of different types of controllers were investigated by Sun et al (2019).…”