Intelligent Control and Tracking Identification of Magnetorheological Damper Based on Improved BP Neural Networks

In view of the inherent nonlinear nature and uncertainty of the semi-active control system based on magnetorheological (MR) fluid damper, an improved back-propagation (BP) algorithm is proposed, which divides the actual structure model into a mechanism model part and a time-varying error model part. By means of off-line training and on-line modifying, an inverse model of MR damper and the intelligent control system based on the improved BP algorithm are acquired. It can be used to predict the damping force of MR damper and eliminate the influence of time delay. Theoretical analysis and numerical simulations show that the intelligent control system can efficiently reduce the structure responses induced by earthquake, has good performance in adaptively tracking target and displays resistance to disturbances