Fuzzy Neural Network Controller for Robotic Manipulators

General defining variables of dynamic fuzzy control systems for robotic manipulators are available within limited ranges.However,it is impossible to tackle with jobs above a limited range.Some clues to solve fuzzy control systems,after analysis,puts forward a new of means control combines nervous net with fuzzy control for robotic manipulators.Random information are gathered to design the fuzzy system.Final simulation results indicate that the DFNN model has fine intelligence performance when applied to robotic control,being able to overcome the effect of some factors,such as nonlinearity,uncertainty,strong coupling existing in robot systems.