Modeling of Nonlinear Systems by Employing Self-Organization and Evaluation — SOR Network—

Abstract

In this paper, an adaptive self-organizing relationship (ASOR) network, which is the extension of the self-organizing relationship (SOR) network proposed by the authors, is proposed. The SOR network can obtain the desired input/output relationship of a target system by using the input/output vector pairs and their evaluations. In order to add the ability of adaptation to the SOR network, the new algorithm that the learning rate and the area of the neighborhood are adjusted according to need is employed. The ASOR network can adapt to the change of the desired input/output relationship of the target system. The effiectiveness of the proposed ASOR network is verified by applying it to design of the control system of the DC motor whose load changes with time.KeywordsWeight VectorOutput LayerInput VectorLearning RateTarget SystemThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.