Semi-active control of smart building-MR damper systems using novel TSK-Inv and max-min algorithms

Two novel semi-active control methods for a seismically excited nonlinear benchmark building equipped with magnetorheological dampers are presented and evaluated in this paper. While a primary controller is designed to estimate the optimal control force of a magnetorheological (MR) damper, the required voltage input for the damper to produce such desired control force is achieved using two different methods. The first technique uses an optimal compact Takagi-Sugeno-Kang (TSK) fuzzy inverse model of MR damper to predict the required voltage to actuate the MR dampers (TSKFInv). The other voltage regulator introduced here works based on the maximum and minimum capacities of MR damper at each time-step (MaxMin). Both semi-active algorithms developed here, use acceleration feedback only. The results demonstrate that both TSKFInv and MaxMin algorithms are quite effective in seismic response reduction for wide range of motions from moderate to severe seismic events, compared with the passive systems and performs better than original and Modified clipped optimal controller systems, known as COC and MCOC.