Car auxiliary control system using type-II fuzzy logic and neural networks

Abstract

In this paper, a Type-II fuzzy and neural network system is introduced to car auxiliary control system for inexperienced drivers. The approach applies Type-II fuzzy logic to generate the training data set for the neural network. The Type-II fuzzy logic is launched by the component called the fuzzy controller. With Type-II fuzzy logic and neural network system, the auxiliary system can manipulate more driving conditions so that enables the neural network to predict more reliably. The results of the approach is compared with Type-I fuzzy/neural system and discussed in detail. © 2006 Springer.