Tracking control of robot manipulators based on orthogonal neural network

A robust adaptive control based on orthogonal neural network (ONN) is presented for robot manipulators in this paper. The adaptive controller constructed by Legendre orthogonal function neural network has some advantages such as simple structure and fast convergence speed. The adaptive learning law of orthogonal neural network is derived to guarantee that the adaptive weight errors and tracking errors are bounded by using Lyapunov stability theory. Simulation results on a two-link robot manipulator validate the control scheme.