5
2005.
ON-LINE IDENTIFICATION OF A ROBOT MANIPULATOR USING NEURAL NETWORK WITH AN ADAPTIVE LEARNING RATE
Abstract This paper proposes an extension of neural network identification capabilities for on-line identification of a nonlinear closed-loop control system. The neural network (NN) is trained on-line using the backpropagation optimization algorithm with an adaptive learning rate. The optimization algorithm is performed at each sample time to compute the optimal control input. The results confirm the effectiveness of the proposed neural network based identification scheme and control architecture.