%0 Journal Article
%T Intelligent Fault Diagnosis of Steer-By-Wire Automobile
%A Fangyuan Wu
%A Feng Kong
%A Jiangyun Yao
%J Journal of Computers
%D 2012
%I Academy Publisher
%R 10.4304/jcp.7.5.1204-1211
%X ¡ªThis paper presents an intelligent fault diagnostic approach for a steer-by-wire (SBW) system. A rough set model is utilized to reduce the redundant information. On the base of the reduction, the classifying rules can be extracted. A radical basis function (RBF) neural network optimized by particle swarm optimization (PSO) algorithm is designed to learn the fault rules that are extracted from the reduction of the redundant information. The proposed approach is simulated in MATLAB. Simulation results show that the proposed intelligent fault diagnostic algorithm provides a higher level of diagnostic accuracy than the approach without any optimization.
%K fault diagnosis
%K steer-by-wire
%K rough set
%K radical basis function neural network
%K particle swarm optimization
%U http://ojs.academypublisher.com/index.php/jcp/article/view/5550