Direct Artificial Neural Network Control of Single Link Flexible Joint

the currently existing methods for control of a flexible joint manipulator have not been desirable precision because of existence of uncertain and nonlinear dynamics. In this paper, we propose an online neural network controller for singlelink flexible joint manipulator. The nonlinear dynamical model of the manipulator is determined by Lagrange's approach, and its order is four; however, the model is uncertain. A multi-layer perceptron neural network consists of three layers with one hidden layer as a controller. The weights of the proposed controller are regulated by back propagation error online approach. The learning rate is carefully selected so that the output response has a minimum oscillation. The control objective is high precision tracking the angular displacement trajectory. The simulation results show the effectiveness of the controller.