A self-constructing fuzzy CMAC model and its applications

This work presents a self-constructing fuzzy cerebellar model articulation controller (SC-FCMAC) model for various applications. A self-constructing learning algorithm, which consists of the self-clustering method (SCM) and the back-propagation algorithm, is presented. The proposed SCM scheme is a rapid, one-pass algorithm which dynamically estimates the number of hypercube cells in input data space. The clustering method does not require prior knowledge, such as the number of clusters in a data set. The back-propagation algorithm is applied to tune the adjustable parameters. Simulation results are obtained to show the performance and applicability of the proposed model.