The paper proposes a new dynamic model based on the LuGre model and an electrical equation to describe the hysteresis phenomenon for a magnetorheological (MR) damper. In addition, a sliding mode observer (SMO) is proposed to estimate unmeasurable states of the MR damper. The parameters of the MR damper are successfully identified by using the self-learning particle swarm optimization (SLPSO) algorithm. The contributions of this paper are: i) a new dynamic model based on the LuGre model and an electrical equation for an MR damper is successfully formulated to fit for the hysteresis behavior, ii) the exerted damping force can be practically adjusted by using input voltage for the dynamic model, iii) the SMO is proposed to estimate the internal states and current, and iv) the unknown parameters of the MR damper are successfully identified by using the SLPSO algorithm with a numerical experiment.
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