BACKSTEPPING ADAPTIVE FUZZY CONTROL FOR UNCERTAIN ROBOT MANIPULATOR

In this paper, two backstepping adaptive fuzzy controllers (BAFCs) are presented for the trajectory tracking of robot manipulator in consideration of its modelling uncertainty and external disturbance. First, the manipulator system is transformed into two first-order subsystems. Second, two adaptive fuzzy controllers based on backstepping method are designed for whether upper bound of the external disturbance is known or unknown, respectively, on the bases of modelling uncertainty. When the upper bound is known, the corresponding controller ensures that the actual trajectory tracks a given desired one with global asymptotical stability. When the upper bound is unknown, another controller guarantees the L2 gain for manipulator system. Finally, the simulation results are given by taking a two-link robot manipulator as an example, this can be used to illustrate its performance of this scheme.