A fuzzy neural networks controller of underwater vehicles based on ant colony algorithm

Owing to the characteristic of autonomous underwater vehicles (AUV) control and to solve the typical nonlinearity control system, we deduced a new fuzzy neual network control based on expert experience and ant colony algorithm. This algorithm superiority in solving combination optimization problems which consists of the rule sets and parameters of the membership functions of the continuous fuzzy controller to be slected. In order to enhance the efficiency of ant colony algorithm and prevent the precocity, the expert experience and improving ant colony algorithm are introduced in. Simulation results and applications showed that method is effective enough to make control simpler and robust and to get good control performance.