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磁流变阻尼器的神经网络建模及应用

The Neural Network Modeling of MR Dampers and Application
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摘要 对非线性的磁流变阻尼器进行建模,建立单个磁流变阻尼器的神经网络正模型和神经网络逆模型,设计了两种四磁流变阻尼器的神经网络逆模型,通过两层控制策略将它们应用于汽车半主动悬架控制.结果表明:第1种神经网络逆模型对簧载质量的垂直加速度、俯仰角加速度和侧倾角加速度具有较好的控制效果,可有效改善车辆的行驶平顺性和操纵稳定性;第2种神经网络逆模型还有待改善. 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.
作者 王昊 史小梅
出处 《上海电力学院学报》 CAS 2010年第1期69-74,共6页 Journal of Shanghai University of Electric Power
基金 上海电力学院科研基金引进人才项目(K2008-47)
关键词 磁流变阻尼器 神经网络 半主动控制 最优控制 整车悬架 MR dampers neural network semi-active control optimal control suspension of full-vehicle model
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参考文献11

  • 1GUO D L,,HU H Y,YI J Q.Neutral network control for asemi-active vehicle suspension with a Magneto-rheologicalDamper. Journal of Vibration and Control . 2004
  • 2IKENAGA S,LEWIS F L,CAMPOS J,et al.Active sus-pension control of ground vehicle based on a full-vehiclemodel. Proceedings of the American ControlConference . 2000
  • 3LAM H F,LIAO W H.Semi-active control of automotive su-spension systems with magneto-rheological dampers. Smart Structures and Materials 2001:Smart Structures andIntegrated Systems . 2001
  • 4DYKE S J,SPENCER B F.A comparison of semi-activecontrol strategies for the MR damper. Proceeding ofIntelligent Information Systems . 1997
  • 5Choi SB,Lee HS,Park YP.H control performance of afull-vehicle suspension featuring magnetorheological dampers. Vehicle System Dynamics . 2002
  • 6Dyke,S. J.,Spencer,B. F.,Sain,M. K.,Carlson,J. D.Modeling and control of magnetorheological dampers for seismic response reduction. Smart Materials and Structures . 1996
  • 7Chang C C,Zhou L.Neural network emulation of inverse dy-namics for a magnetorheological damper. Journal of Struc-tural Engineering,ASCE . 2002
  • 8XIA Pin-qi.An inverse model of MR damper using optimal neural network and system identification. Journal of Sound and Vibration . 2003
  • 9Spencer B F,Dyke S J,Sain M K,et al.Phenomenological model of a magnetorheological damper. Journal of Engineering . 1997
  • 10Yao G Z,Yap F F,Chen G,et al.MR damper and its application for semi-active control of vehicle suspension system. Mechatronics . 2002

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