Parameter Estimation and its Sensitivity Analysis of the MR Damper Hysteresis Model Using a Modified Genetic Algorithm

Abstract

The recently developed magnetorheological (MR) dampers serve as an ideal candidate for diverse applications including structural vibration suppression, shock absorption, and vibration control in vehicle systems. Previous research indicates that they are characterized with non-linear hysteresis and this was further testified in the present study. Various models have been proposed to interpret the complex characteristic, but they are plagued by certain limitations. In view of this, the present study sets out to propose a more efficient genetic algorithm (GA) and a simplified Bouc—Wen model. And it moves to adopt and improve the GA by some effective methods including effective selection methods, adaptive genetic operators and appropriate termination criteria. Then the simplified Bouc—Wen model is obtained by fixing the values of the insensitive parameters in the original model based on the sensitivity analysis theory. Finally, the experimental data of the MR damper responses verify that the proposed approaches are capable of efficient computations and accurate parameter estimation. Also suggested are the implications of the present study on other novel smart dampers.

Keywords

MR damper Bouc—Wen model parameter estimation sensitivity analysis genetic algorithm.

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