【摘要】 根据磁流变阻尼器力学性能测试结果,建立磁流变阻尼器滞回参数模型。以阻尼力为优化目标,采用粒子群算法进行参数识别。结果显示,粒子群算法的参数识别精度高、辨识速度快,是理想的非线性参数辨识工具;研究表明,提出的磁流变阻尼器改进滞回参数模型效果较好,能很好地描述阻尼力的滞回特性。更多还原

【Abstract】 According to test results of magnetorheological damper(MRD), the hysteresis parameters model is established to describe the mechanical properties of MRD. Focusing the optimization goal to damping force, the parameters of model have been identified using the particle swarm optimization(PSO) algorithm. Results show that PSO have high identification precision and quickly identification speed, which is the ideal nonlinear parameter identification tool. Results also indicate that the damping force hysteresis characteristics of MRD can be accurately described by the proposed hysteresis parameters model of MRD更多还原