• CN:11-2187/TH
  • ISSN:0577-6686

›› 2005, Vol. 41 ›› Issue (5): 31-37.

• 论文 • 上一篇    下一篇

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基于磁流变减振器的汽车半主动悬架非线性控制方法

李以农;郑玲   

  1. 重庆大学机械传动国家重点实验室
  • 发布日期:2005-05-15

NONLINEAR CONTROL METHODS OF AUTOMOTIVE SEMI-ACTIVE SUSPENSION BASED ON THE MR DAMPER

Li Yinong;Zheng Ling   

  1. State Key Laboratory of Mechanical Transmission, Chongqing University
  • Published:2005-05-15

摘要: 考虑磁流变减振器阻尼力和悬架弹性元件非线性特性,建立车辆半主动悬架非线性动力学模型。应用微分几何非线性控制,经过适当的非线性状态和反馈变换,实现半主动悬架非线性系统的精确线性化,并对系统实施非线性状态反馈控制;根据预定的控制目标及模糊控制策略调节控制参数,设计模糊控制器, 对悬架系统进行了控制仿真研究;利用神经网络模式识别能力对输入数据处理辨别,设计控制网络层,从而达到提高悬架工作性能,改善汽车行驶舒适性的目的。将三种非线性控制方法的仿真结果进行分析比较表明:经模糊控制或神经网络控制后的悬架承受的冲击响应小、振动强度低,比微分几何控制能获得更优异的性能。

关键词: 半主动悬架, 磁流变减振器, 非线性控制, 模糊, 神经网络, 微分几何

Abstract: The nonlinear dynamic model of automotive semi-active suspension is established with considering of the nonlinear characteristics of the MR (Magnetorhelogical) damper and the nonlinear rigidity of springiness element. At first, the non-linear control strategy of differential geometry theory is applied to execute feedback control on the semi-active suspension. The nonlinear model of the semi-active suspension is transferred to a simple linear system through a nonlinear state feedback. Then, according to the road excitation, the predetermined control object and the fuzzy control strategy to adjust the fuzzy logic control parameters, the fuzzy controller is designed. Furthermore, the neural network controllers are designed to improve automotive ride comfort. Finally, the simulation results are made a comparison between three non-linear control methods. It is shown that the suspension used fuzzy logic and neural network control methods has less impact response and lower vibration intensity than differential geometry theory control strategy, and has more superior performance.

Key words: Differential geometry, Fuzzy logic, MR damper, Neural network, Non-linear control, Semi-active suspension

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