Journals Proceedings

Abstract

Magnetorheological (MR) dampers are semi-active devices that can be used to control the response of structures during seismic loads. They have the adaptability of active devices and stability and reliability of passive devices. One of the challenges in the application of the MR dampers is to develop an effective strategy of control that can fully exploit the capabilities of the MR dampers. This paper investigates the effectiveness of an adaptive strategy of control for modulating the command voltage of Magnetorheological dampers which are employed as semi-active devices in combination with laminated rubber bearings for the seismic protection of buildings. The controller developed in this study is an adaptive fuzzy neural controller (AFNC). It consists of a direct fuzzy controller with self-tuning scaling factors based on neural networks. A simple feed forward neural network is implemented to adjust the input scaling factors such that the fuzzy controller effectively determines the command voltage of the damper according to the current level of ground motion. For the purpose of comparison, a passive operation is also considered in simulating maximum voltage operation of MR damper. The results reveal that the developed adaptive controller can successfully improve the seismic response of base-isolated buildings against various types of earthquake.