摘要
为了提高车辆自动控制能力,提出基于神经网络下的车辆自动控制系统决策算法。构建车辆自动控制系统的行驶动力学和运动学模型,以相位偏移和惯性转矩为约束参量构建车辆自动控制系统模糊反馈误差跟踪融合控制律,采用模糊参数融合和自适应参数调节方法进行车辆自动控制系统决策和模型预测,采用变结构神经网络控制的方法进行车辆自动控制系统的模糊决策构造,建立车辆自动控制系统决策的约束参数优化模型,采用自适应模糊跟踪融合识别方法进行车辆自动控制系统决策的参数寻优,实现车辆自动控制系统的优化决策控制。仿真结果表明,采用该方法进行车辆自动控制系统决策控制的自适应性性较好,控制输出的鲁棒性较强。
In order to improve the automatic control ability of the vehicle,a decision-making algorithm of the vehicle automatic control system based on the neural network is proposed.The driving dynamics and the kinematic model of the vehicle automatic control system are constructed,and the fuzzy feedback error tracking and fusion control law of the automatic control system of the vehicle is constructed by using the phase offset and the inertia torque as the constraint parameters.The fuzzy parameter fusion and the self-adaptive parameter adjustment method are adopted to carry out the decision and model prediction of the vehicle automatic control system.The fuzzy decision structure of the automatic control system of the vehicle is carried out by adopting a variable structure neural network control method.A constraint parameter optimization model for the decision of the automatic control system of the vehicle is established.The parameter optimization of the vehicle automatic control system decision-making is carried out by the self-adaptive fuzzy tracking fusion recognition method,and the optimization decision-making control of the vehicle automatic control system is realized.The simulation results show that the proposed method is adaptive to decision contvol and robust to control output.
作者
晋军
JIN Jun(Technology Center,Shaanxi Automobile Holding Group Co.,Ltd.,Xi'an 710200)
出处
《环境技术》
2020年第2期16-20,共5页
Environmental Technology
关键词
神经网络
车辆
自动控制系统
决策算法
neural network
vehicle
automatic control system
decision-making algorithm
作者简介
晋军(1992.2-),男,工程师,研究方向:智能网联/人工智能,自动驾驶。
