신경망제어를 이용한 MR 댐퍼 기반 스마트 제진 시스템의 내진 성능 평가

In this paper, a semiactive modal neuro-control scheme which combines the modal neuro-control algorithm with a semiactive control device (i.e., a magnetorheological (MR) fluid damper) is proposed, and its effectiveness is experimentally verified through a series of shaking table tests. A modal neuro-control scheme uses modal coordinates as inputs of neuro-controller. Hence, it is more convenient to design a controller compared with conventional neuro-control schemes. A Kalman filter and a low-pass filter are introduced to estimate modal states from measurements by sensors and to eliminate the spillover problem, respectively. Moreover, the clipped algorithm is adopted to provide an appropriate command voltage to an MR fluid damper. For shaking table tests, a scaled three-story shear building model with an MR fluid damper is considered. Two types of semiactive modal neuro-controllers are trained with the reproduced El Centro earthquake for their own purposes. The performance of the proposed semiactive modal neuro-control scheme is compared with that of the passive-off, passive-on, and passive-optimal cases. It is clearly demonstrated from the experimental results that the proposed semiactive modal neuro-control system shows the better control performance than other control cases over the entire range of earthquake intensities considered.