Experimental study of robot manipulators based on robust adaptive control
Weidong Chen · 2005
A radial basis function (RBF) network-based adaptive tracking control scheme is proposed for robot manipulators. A RBF network is used to generate control input signals that are similar to the control inputs of adaptive control using linear reparameterization of the robot manipulator. A sliding model control term is used to eliminate the effects of the network inherent approximation errors and external disturbance. The asymptotic stability of the control system is established using Lyapunov theorem. Experiments are given on a two-link robot in the end of paper, and validated the control arithmetic.