汽车半主动空气悬架自适应模糊神经网络控制

Self-adaptive fuzzy neural network control for automotive semi-active air suspension

考虑空气悬架弹簧刚度可调的特性,建立了车辆5自由度的半主动悬架非线性动力学模型.提出了一种基于自适应模糊神经网络系统结构的模型,参考自适应控制方法来研究汽车半主动空气悬架的非线性控制问题,并考虑半车模型前后悬架的输入时滞,对其进行了仿真分析.研究结果表明:该控制方法能够使人体垂直加速度、车身垂直加速度和俯仰角加速度都得到很大的衰减,可在一定程度上减少路面对车身的振动冲击,提高汽车的行驶平顺性.

Considering the adjustable characteristics of air springs, a 5 - DOF nonlinear semi - active model is established. A kind of model reference control method based on a Self - Adaptive Fuzzy Neural Network is put forward to solve the air suspension control problem. The system is simulated taking the input time delay of front and rear air suspension of the half - vehicle model into account. The result shows that the Self - Adaptive Fuzzy Neural Network control method can reduce the vertical acceleration of the human and vehicle bodies and the pitch angular acceleration, and hence improve the ride comfort of the vehicle to a higher extent.