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,建立了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,改善车辆行驶舒适性的目的。将3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的悬架冲击响应小、振动强度低,比微分几何控制能获得更优异的性能。
A nonlinear dynamic model of automotive semi-active suspension was established with considerations 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 was applied to execute feedback control on the semi-active suspension. The nonlinear model of the semi-active suspension was transferred to a simple linear system through a nonlinear state feedback. Then, according to the road excitation, the preset control object and the fuzzy control strategy, the fuzzy logic control parameters were adjusted and the fuzzy controller was designed. Furthermore, the neural network controllers were designed to improve automotive ride comfort. Finally, the simulation results from the three non-linear control methods were compared, which showed that the suspension controlled by the fuzzy logic or the neural network method had less impact response and lower vibration intensity than that by the differential geometry theory strategy, and had superior performance.
出处
《农业机械学报》
EI
CAS
CSCD
北大核心
2005年第5期9-15,共7页
Transactions of the Chinese Society for Agricultural Machinery
基金
*国家自然科学基金资助项目(项目编号:50475064)
重庆市自然科学基金资助项目(项目编号:8366)
2002年重庆大学骨干教师基金资助项目(项目编号:325)
