Robot manipulator controller based on fuzzy neural and CMAC network

A new controller is proposed to deal with the uncertainty in robot manipulator dynamic system. This controller is composed of fuzzy neural network (FNN) controller which replaces computed torque controller, cerebellar model articulation (CMAC) controller which compensated control error online and slide mode controller which compensates fuzzy neural network fit error to enhance robustness of the control system. It is shown that this controller outperforms conventional fuzzy controller by improving learning ability that the conventional fuzzy system does not have with simulations of a two-link manipulator.