Asymptotic Convergence of Feedback Error Learning Method and Improvement of Learning Speed.

Abstract

This paper deals with the improvement of learning speed based on the analysis of convergence of the feedback error learning method. We derive and obtain the condition for the asymptotic convergence of the feedback error learning method for each trial. This condition is the relationship between the learning rate and the α function, which is calculated from the input-output relationship of the system. Using the α function, we propose a high-speed learning method for a tracking control system. We present the simulation results for the tracking control system of a one-link robot manipulator for two cases as follows : (1) use of the general feedback error learning method and (2) use of the proposed high-speed learning method. The simulation results show the effectiveness of the proposed conditions and learning method.