摘要
针对参数化模型不能直接反映阻尼器逆向动态特性、非参数化建模需大量试验数据问题,提出两者结合模型。该模型用自适应神经模糊系统建立位移、速度对阻尼力的非线性表达模型,用参数化方法描述阻尼力随电压及速度的变化输出模型。研究表明,此建模方法能较好逼近磁流变液阻尼器试验结果并反映其非线性特性,便于实际控制,且可减少计算工作量。
Aiming at strong non-linear characteristics of magneto-rheological（ MR） dampers,building an effective model is a key to use them in practical engineering. Both a parametric model and a non-parametric model have their own drawbacks,a new model combining both of them was proposed here. In this new model,an adaptive neural-fuzzy inference system（ ANFIS） was adopted to build a non-parametric model to describe the effect of displacement and velocity on damping force,the parametric method was used to describe the maximum damping force in relation to the voltage and the maximum rod speed. The results showed that this modeling method has good results approaching to MR dampers test ones,and can well reflect the non-linear characteristics of MR dampers; this method is convenient for actual control and it can reduce the calculation cost.
出处
《振动与冲击》
EI
CSCD
北大核心
2015年第6期36-40,共5页
Journal of Vibration and Shock
基金
国家自然基金项目(51375212)
江苏省动力机械清洁能源与应用重点实验室开放基金项目(QK13003)
作者简介
潘公宇 男，博士，教授，1965年1月生
