车辆主动悬架控制策略的联合仿真研究

Research on Co-Simulations of Controlling Strategy for Vehicle Active Suspension

根据PID控制原理、模糊控制理论和神经网络控制理论,建立主动悬架单神经元控制器和神经网络PID控制系统,主要是利用S函数建立了主动悬架单神经元控制器;并建立了由三层BP神经网络进行在线辨识,并在此基础上建立对神经PID控制器权值进行在线调整的在线辨识神经PID控制系统,并进行联合仿真,将其输出的振动加速度等参数与传统的PID控制策略进行分析和比较,模糊控制理论和神经网络控制理论的应用对悬架的平顺性有更好的改善作用,也说明了采用联合仿真方法的有效性和准确性。

Based on PID domination principle、fuzzy control theory and neural network control theory active suspension with the single neuron controller and neural PID-controller is structured,active suspension with the single neuron controller is structured by means of s-function.Furthermore,online identification neural network control system is structured by means of the online identification function of three-layer BP neural network,on the basis of it,weight of neural PID-controller is adjusted online and proceed with Co-simulation,The output of parameters data such as vibration acceleration is analyzed and compared with traditional PID-controller,The application of fuzzy control theory and neural network control theory have a better improvement for ride comfort,and proved effectiveness and accurateness of co-simulation.