Vibration suppression of a structure with an MR damper using a neural network controller

Semi-active vibration control has attracted a great deal of attention taking advantage of vibration reduction effect, control stability and effective energy consumption. MR dampers are known as one of semi-active control devices, which consist of controllable fluids in fixed orifice dampers. In this paper, response reduction is numerically and experimentally conducted on a building structural model equipped with an MR damper on the first story. It is difficult to deal with time variation of properties and nonlinearities of MR dampers and structures. It is another problem that optimal damping may be varied according to frequency and magnitude of components of a wave input to structures. In order to deal with these problems, neural networks are applied to the vibration control system. As a result, it is shown that the displacement of the top story of the structure is highly reduced using the neural network control system.