Neural Networks Based on TrigonometricSeries for the Control of a Robot

Abstract

This work shows the design and implementation of a new neural network design based on trigonometric series expansion proposed by Dr. P. Ponce that was applied to control a non linear system (hexapod). In order to prove the capacity of the topology simulation and experimental results are shown. The new topology of the neural network genereted excellent response under new situations presented to the hexapod. A complete description of the topology proposed is presented and explained in detail.