semi-active control of an offshore platform under wave forces incorporating intelligent inverse dynamic model of magnetorheological dampers

magneto rheological (mr) damper is a control device to suppress the vibration of structures. a novel intelligent semi-active control system for the offshore platform utilizing mr damper to enhance desired displacement is proposed. due to inherent non-linear nature of the mr dampers, an intelligent non-linear neuro-fuzzy (nf) control strategy is constructed to control wave-induced vibration of the platform. in the proposed control system, a dynamic-feedback neural network with fuzzy controller is adapted to inverse model of non-linear dynamic of the mr dampers. the control voltage of the dampers are determined by the fuzzy logic controller and the neural netwrok is used to prediction of desired forces. the fuzzy logic rules are extracted based on sugeno inference engine. the essential feature of the proposed intelligent control strategy is its ability to handle the non-linear behavior of the dampers. besides, no mathematical model needed to calculate forces generated by mr dampers. to verify the performance of the nf strategy, comparisons with existing semi-active techniques are made. the typical control strategy is clipped optimal control algorithm, while inherent time-delay and non-linear properties of mr damper lie in these strategies. simulation results demonstrated that the intelligent strategy has better control performance than the clipped algorithm.