Magnetorheological (MR) damper is an ideal semi-active control device for vibration suppression. The mechanical properties of this type of devices show strong nonlinear characteristics, especially the performance of the small-scale dampers. Therefore, developing an ideal model that can accurately describe the nonlinearity of such device is crucial to control design. In this paper, the dynamic characteristics of a small-scale MR damper developed by our research group is tested, and the Stribeck effect is observed in the low velocity region. Then, an improved model based on sigmoid model is proposed to describe this Stribeck effect observed in the experiment. After that, the parameters of this model are identified by genetic algorithms, and the mathematical relationship between these parameters and the input current, excitation frequency and amplitude is regressed. Finally, the predicted forces of the proposed model are validated with the experimental data. The results show that this model can well predict the mechanical properties of the small-scale damper, especially the Stribeck effect in the low velocity region.

Magnetorheological (MR) dampers are increasingly employed to attenuate the harmful vibration in Civil Structures caused by dynamic loadings such as earthquakes and strong winds for their excellent response mitigation capacity. The credibility and precision of dynamic response mitigation capacity of MR dampers are highly dependent on intelligent control strategy. In this paper, a piecewise control algorithm based on the feedbacks of story drift and ground excitation acceleration is adopted through a micro-controller with a digital signal processor chip as the control processor. Shaking table tests are carried out on a three-story steel frame structure which incorporates MR damper with the micro-controller installed between the ground and first floor. The dynamic responses of the real-time online intelligent controlled structure are compared with those of passive-on and passive-off controlled structures under different earthquake waves to evaluate vibration control efficacy of the MR intelligent control system. Test results show that the developed MR intelligent control system can sufficiently reduce the peak and root mean square responses due to earthquake excitations, and the control efficiency of displacement and acceleration responses is higher than the two passive control cases.

An efficient optimization design method for magnetorheological (MR) dampers, aimed at enhancing the damping force output and the adjustable coefficient, is explored in this study. The structural parameters of the double-rod MR damper, which significantly influence dynamic performance, were systematically analyzed and determined through Sobol Sensitivity Analysis. On this basis, the critical parameters were automatically optimized using Non-Dominated Sorting Whale Optimization Algorithm. By analyzing the unified Pareto front, the optimal structural parameters of the MR damper are determined and verified through numerical simulations and experimental comparisons. The results show that the key parameters affecting the mechanical performance of MR dampers can be reduced to five. The MR damper designed with these optimal parameters demonstrated a 17.1% increase in the adjustable coefficient and a 1.6-fold increase in damping force. Additionally, the optimization design method exhibited notable computational efficiency with superior global convergence characteristics, effectively solving the challenges in the optimization design of MR dampers. This study further deepens the optimization design theory of MR dampers and broadens the potential for diverse engineering applications.