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《Journal of Shanghai University of Electric Power》 2010-01
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The Neural Network Modeling of MR Dampers and Application

WANG Haoa,SHI Xiao-meib(a.School of Thermal Power and Environmental Engineering,b.School of Computer and Information Engineering,Shanghai University of Electric Power,Shanghai 200090,China)  
In order to model the nonlinear MR damper,the neural network models for the direct model and the inverse model of a single MR damper are created respectively.On this basis,two different recurrent neural network(RNN) inverse models for four MR dampers are designed and applied to the control of the semi-active suspension of the full-vehicle model.The simulation results demonstrate that the first RNN inverse model can greatly reduce the vertical acceleration and pitch angular acceleration and roll angular acceleration of the sprung-mass so that the ride comfort and handling of the semi-active suspension can be dramatically improved.However,there is still room for improvement for the second RNN inverse model.
【Fund】: 上海电力学院科研基金引进人才项目(K2008-47)
【CateGory Index】: TB535.1
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【Co-citations】
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