Asymptotic convergence of feedback error learning method considering spillover in controlling flexible structure

This paper deals with the spillover effect to the asymptotic convergence of the feedback error learning method for trajectory control of the flexible structure by the neural network. The conditions for the asymptotic convergence of feedback error learning method for each trials are obtained. The influence of the vibration modes unmodeled on the conditions for the asymptotic convergence is discussed. Based on the results obtained here, we present a new learning method to improve the control performance. The control system consists of a low pass filter and two neural networks. The learning method is to change the learning rate according to the convergence conditions. From simulation results, we show that the tracking performance is improved by using the proposed learning method.