Semi-active neuro-control for base-isolation system using magnetorheological (MR) dampers

Vibration mitigation using smart, reliable and cost-effective mechanisms that requires small activation power is the primary objective of this paper. A semi-active controller-based neural network for base-isolation structure equipped with a magnetorheological (MR) damper is presented and evaluated. An inverse neural network model (INV-MR) is constructed to replicate the inverse dynamics of the MR damper. Next, linear quadratic Gaussian (LQG) controller is designed to produce the optimal control force. Thereafter, the LQG controller and the INV-MR models are linked to control the structure. The coupled LQG and INV-MR system was used to train a semi-active neuro-controller, designated as SA-NC, which produces the necessary control voltage that actuates the MR damper. To evaluate the proposed method, the SA-NC is compared to passive lead-rubber bearing isolation systems (LRBs). Results revealed that the SA-NC was quite effective in seismic response reduction for wide range of motions from moderate to severe seismic events compared to the passive systems. In addition, the semi-active MR damper enjoys many desirable features, such as its inherent stability, practicality and small power requirements. The effectiveness of the SA-NC is illustrated and verified using simulated response of a six-degree-of-freedom model of a base-isolated building excited by several historical earthquake records. Copyright (C) 2006 John Wiley & Sons, Ltd.