Improving PID Controller Using Neural Network Technique

Authors

  • Uchegbu C. E  Department of Electrical and Electronic Engineering, Abia State Polytechnic, Aba, Nigeria
  • Ekwuribe J. M  Department of Electrical and Electronic Engineering, Abia State Polytechnic, Aba, Nigeria
  • Ogbonnaya I. J  Department of Electrical and Electronic Engineering, Abia State Polytechnic, Aba, Nigeria

Keywords:

PID, NN, Simulation, MAT-LAB

Abstract

This research focuses on improving the quality of traditional Proportional integral derivative (PID) using neural network. A Reverence model approach was used to design a Neural Network NN controller and a proportional integral derivative PID controller. The purpose is to have a stable control systems in our industries that will help to improve and reduce waste during production in our industries that will be more flexible in the level of conversion, to be able to track set point change and reject load disturbance in our process industries. PID control scheme was used as a benchmark to study the performance of the PID controller at the same time with equivalent neural network. The proportional Integral derivative controller PID was modeled using Neural Network Technique NN and a MAT-LAB simulation was carried out and observation showed that there was a great improvement on the traditional PID controller as it started functioning like a digital controller. When connected to the Plant process control were all features of the traditional proportional integral derivative PID controller were retained and as well improved using Neural Network . The output was fantastic since the waste and loss encored by the process industries was drastically reduced to minimal.

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International Journal of Scientific Research in Science, Engineering and Technology

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Published

2016-12-30

Issue

Volume 2, Issue 6, November-December-2016

Section

Research Articles

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How to Cite

[1]
Uchegbu C. E, Ekwuribe J. M, Ogbonnaya I. J, " Improving PID Controller Using Neural Network Technique, International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 2, Issue 6, pp.576-580, November-December-2016.