Fuzzy neural network control of truck backer-upper using hybrid genetic algorithms

Abstract

In this paper, a kind of fuzzy neural network based on hybrid genetic algorithms is proposed. Hybrid genetic algorithm is presented to train the fuzzy neural network. The hybrid genetic algorithm improved normal genetic algorithm. The BP algorithm is added to genetic algorithm. In particularly, the global convergent characteristic of the genetic algorithm is used to find the possible universal optimum, and the great feature of the BP algorithm, that is, error descend in the direction of grads, is used to fast search about the optimum. Thus, the fast learning capability and an accurate approximation ability are obtained. The fuzzy neural network is used to the control problem of truck backer-upper. The simulation results show that it achieves better control effect.