Development and Control of Magnetorheological Elastomer-Based Semi-active Seat Suspension Isolator Using Adaptive Neural Network

The present study aims at the development of a magnetorheological elastomer (MRE) based semi-active seat suspension isolator and its adaptive control using a neural network (NN) control scheme. Isotropic MRE samples with 25% volume fraction of iron particles have been fabricated and then characterized under shear mode using a rotary magneto-rheometer to obtain MRE's viscoelastic properties (shear storage and loss moduli) under different levels of applied magnetic flux density. Results reveal a significant change in the storage and loss moduli with respect to the varied magnetic field. The viscoelastic properties of the MRE are then utilized to design an MRE-based seat suspension isolator in order to attenuate the transmitted vibration to the driver. For this purpose, the modeling of the seat incorporated with the MRE-based isolator is derived and subsequently, a novel NN control scheme is proposed for the semi-active control of the MRE-based isolator. The convergence and stability of the proposed control strategy have been mathematically verified using the Lyapunov method. Finally, the performance of the proposed control strategy is compared with those obtained using passive and widely used sky-hook controllers under different types of excitation including harmonic motion, road bump, and random profile. It is shown that the proposed NN controller considerably mitigates the vibration of the driver seat and outperforms the passive and skyhook controllers over the frequency range of interest.