关键词: 车辆工程, 主动悬架, 饱和非线性, 多层神经网络, 自适应控制

Abstract: The vibration damping performance of active suspension system was seriously restricted by nonlinearity of actuator saturation, which even destabilized the system. The saturation characteristic of system actuator was described by the standard saturation function expression. The dynamic model of active suspension system for 1/4 vehicle body with state feedback of actuator saturation was established, and then the proposed model was transformed into an equation of state with approximate Brunovsky standard. Multi-layer neural network method was used to design the adaptive controller. The adaptive tracking of controller, the robustness of controller under different saturation, the influence of control parameters on the controller and the adaptive effect of controller under random excitation were simulated and studied by using the designed controller. The research results show that the error between output response of system and target value is small, and the controller tracking effect is good. As the saturation decreases, the robustness of system decreases. The selection of control parameters affects the output response of system, and determines the selection range of the main control parameters. The proposed controller still has good adaptive effect under random excitation. This paper can provide some theoretical references for the study on saturation nonlinearity of active suspension system.

Key words: vehicle engineering, active suspension, saturation nonlinearity, multi-layer neural network, adaptive control