Volume 1, Issue 2, December 2016, Page: 20-26
Remoldelling of PID Controller Based on an Artificial Intelligency (Neural Network)
Uchegbu C. E., Department of Electrical and Electronic Engineering, Abia State Polytechnic, Aba, Nigeria
Eneh I. I., Department of Electrical and Electronic Engineering, Enugu State University of Science and Technology, Enugu, Nigeria
Ekwuribe M. J., Department of Electrical and Electronic Engineering, Abia State Polytechnic, Aba, Nigeria
Ugwu C. O., Department of Electrical and Electronic Engineering, Enugu State University of Science and Technology, Enugu, Nigeria
Received: Sep. 30, 2016;       Accepted: Nov. 30, 2016;       Published: Dec. 21, 2016
DOI: 10.11648/j.ajset.20160102.12      View  4038      Downloads  144
Abstract
The proportional integral derivative PID controller remodeled using Neural Network and easy hard ware implementation, which will improve the control system in our industries with a high turnover. However, in this work, we propose a non-linear control of stochastic differential equation to Neural Network matching; the model has been validated, evaluated and compared with other existing controllers. The idea is to have control systems that will be able to achieve, improve, reduce waste and that is more flexible in the level of conversion, to be able to track set point change and reject load disturbance in our process industries. This paper represents a preliminary effort to design a simplified neutral network and proportional integral derivative PID control scheme, and modeling, their operational characteristics for a class of non-linear process. At the end we were able to achieve a good result by remodeling the proportional integral derivative PID controller with Neural Network Technique, and connected the plant process control where all the features of the traditional proportional integral derivative PID controller were retained and as well improved using MAT-LAB. The output was fantastic since the waste and loss encored by the process industries was drastically reduced to minimum.
Keywords
PID, Neural Network, Model, Controller, Simulation, MAT-LAB
To cite this article
Uchegbu C. E., Eneh I. I., Ekwuribe M. J., Ugwu C. O., Remoldelling of PID Controller Based on an Artificial Intelligency (Neural Network), American Journal of Science, Engineering and Technology. Vol. 1, No. 2, 2016, pp. 20-26. doi: 10.11648/j.ajset.20160102.12
Copyright
Copyright © 2016 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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