This paper addresses the problem of micro-vibration control of a precision vibration isolation system with a magnetorheological elastomer (MRE) isolator and fuzzy control strategy. Firstly, a polyurethane matrix MRE isolator working in the shear-compression mixed mode is introduced. The dynamic characteristic is experimentally tested, and the range of the frequency shift and the model parameters of the MRE isolator are obtained from experimental results. Secondly, a new semi-active control law is proposed, which uses isolation structure displacement and relative displacement between the isolation structure and base as the inputs. Considering the nonlinearity of the MRE isolator and the excitation uncertainty of an isolation system, the designed semi-active fuzzy logic controller (FLC) is independent of a system model and is robust. Finally, the numerical simulations and experiments are conducted to evaluate the performance of the FLC with single-frequency and multiple-frequency excitation, respectively, and the experimental results show that the acceleration transmissibility is reduced by 54.04% at most, which verifies the effectiveness of the designed semi-active FLC. Moreover, the advantages of the approach are demonstrated in comparison to the passive control and ON-OFF control.

Due to the controllability of the stiffness and damping under the applied magnetic field, magnetorheological elastomer isolator has been proved effective in the field of vibration control. For the realization of vibration control application, an accurate MRE isolator model is a non-trivial task. However, the existing parametric modeling methods are required to identify too many parameters, which are difficult to implement. Moreover, the corresponding inverse dynamic model of the isolator cannot even be obtained by the identified model inversion. Therefore, this paper proposes a nonparametric neural network approach to approximate the dynamic behaviors of magnetorheological elastomer isolator with the characteristics of nonlinearity and hysteresis. Firstly, the dynamic characteristics of the isolator in shearcompression mixed mode are experimentally tested under different loading conditions. Secondly, based on the experimental data, a NARX neural network with three-layer structure is developed to approximate the functional relationship between inputs (displacement, velocity and current) and output (force) of magnetorheological elastomer isolator. Thirdly, the effectiveness of the network model is validated by comparing the predicted force and experimental force. Finally, considering the common occurrence of inputs with noise disturbance in real application, the robustness of the network is also verified for displacement and current inputs with noise disturbance, respectively. The results of the network generalization for experimental data show that the proposed NARX network is more robust and optimal than BP network.

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Protecting high-tech facilities from micro-vibrations in the working environment has demanded intensive research in recent years. One of the most promising devices proposed for facilities protection is the magnetorheological elastomer (MRE) isolator. To explore fully their potentials in the real-time control implementations, control strategy plays an important role. This paper proposes a nonlinear self-tuning fuzzy controller (STFC) for a MRE micro-vibration isolation system exposed to time-varying (variable frequency and amplitude) sinusoidal excitations. The silicone rubber matrix MRE isolator with low initial modulus is employed to suppress the timevarying vibration at low frequency, the performance of the proposed isolator is evaluated by sweep frequency experiments. Different from the conventional fuzzy controller (FC) with fixed parameters, which is only effective for the vibration with a certain frequency and amplitude, a STFC composed of semi-active FC and self-tuning law can suppress time-varying vibration with the wide frequency and amplitude range. In order to achieve the adaptability of the proposed controller to time-varying excitation in real time control, the nonlinear self-tuning law is designed by using genetic algorithm to optimize scaling factors. Both numerical simulations and experiments are conducted to verify the effectiveness of the designed controller. Meanwhile, the control effects between STFC and conventional FC are compared in acceleration attenuation to demonstrate the superiority of the proposed STFC. The results show that the designed nonlinear STFC is more effective for suppressing the time-varying vibration with the amplitude of 0.5-3 m s −2 and frequency of 45-60 Hz.