基于模糊推理理论的线控系统网络健康度研究

Research on Network Health Degree of X-By-Wire System Based on Fuzzy Inference System

线控系统采用基于时间触发机制的总线通信方式进行信号传输,对于通信系统的可靠性与实时性要求很高。引入网络健康度这个概念,作为线控系统网络在线故障诊断的指标,集成于线控系统网络通信的预测策略中,对于提高线控系统的可靠性与实时性具有重要的意义。当进行Flexray通信的总线上外加干扰时,通信网络中就会出现错误帧等问题。总线历史数据输入自适应神经网络模糊推理系统(ANFIS)得到的模糊控制规则,加入到Flexray通信的开发板组成的节点中,就进行线控系统网络通信健康度的有效划分。最终实验结果的证明,利用ANFIS算法,可以实现对线控系统的网络健康度进行合理的预测。

In x-by-wire system, signals are transmitted on bus based on the time triggered mechanism, so the reliability and real-time performance of communication system is important to the system. The concept of network health degree is regarded as an index of network online fault diagnosis for the steer by wire system. By Integrated to the online diagnosis strategy of network communication, network health degree is significant to improve the reliability and real-time of x-by-wire system. When external interference is added to the Flexray network, errors then appear. With historical data input to adaptive neural fuzzy inference system(ANFIS) and fuzzy control rules added to the Flexray communication node, network health degree can be effectively divided. Experimental results prove that ANFIS algorithm is helpful to estimate network health degree of x-by-wire system.