Control of Robot Manipulators Based on Legendre Orthogonal Neural Network

Abstract

In this paper, Legendre orthogonal functions neural network is used to achieve the control of nonlinear systems. The adaptive controller is constructed by using Legendre orthogonal functions neural network. The adaptive learning law of orthogonal neural network is derived to guarantee that the adaptive weight errors and tracking errors are bound by using Lyapunov stability theory. Simulation results are given for a two-link robot, and the control scheme is validated.