A design Neurofuzzy controller for level process control

Abstract

This paper presents the design and implementation of Neurofuzzy controller self-organizing for tuning the fuzzy logic parameter using back-propagation neural network. The controller is implemented by software on a microcomputer to control the unknown transfer function system of real plant for testing the learning efficiency of self-organizing and proper parameter tuning that scaling factor(g0, g1) is set from experimental corresponded with process characterization and designer experience. The results are shown that the performance of this controller improved in term of set point compared with PID standard controller.