汽车智能防撞自适应控制研究与仿真  

Research and Simulation of Vehicle Intelligent Crash-avoiding Self-adaptive Control

作　　者：张学军[1] 郑丽英[1] 

机构地区：[1]兰州交通大学电子与信息工程学院,兰州730070

出　　处：《计算机工程》2010年第9期171-172,175,共3页Computer Engineering

基　　金：甘肃省自然科学基金资助项目"基于RoughSet的软计算方法融合研究"(3ZS042-B25-038);甘肃省教育厅研究生导师科研基金资助项目"基于智能处理的软计算方法融合研究"(0704-13)

摘　　要：针对汽车防撞模糊控制模型不能自动调整参数的缺点,建立汽车防撞自适应模糊推理模型。采用混合学习算法对自适应模糊推理模型的前提参数和结论参数进行辨识,以加速收敛。经模拟训练和仿真输出结果证明,该模型能够对汽车防撞模糊控制器隶属函数和模糊规则进行优化,较好地实现紧急报警情况下的汽车防撞自适应控制。Aiming at defects of vehicle crash-avoiding fuzzy control model whose membership and fuzzy rules can not be adjusted by itself,a vehicle crash-avoiding adaptive network fuzzy interference system model is presented.The hybrid learning algorithm is proposed to improve rapidity of convergence.For some linear parameters such as consequent parameters,recursive least square algorithm is used to update it.For other nonlinear parameters such as premise parameters,steepest descent method are used to identity it.By comparing the simulation result and experiment data,it shows that the membership function and fuzzy rules for fuzzy control model is optimized effectively by using adaptive network fuzzy inference system.It has a good and self-adaptive performance for vehicle auto-control under the dangerous condition.

关 键 词：自适应网络模糊推理系统 汽车智能防撞控制 自适应模糊控制 

分 类 号：TP312[自动化与计算机技术—计算机软件与理论]