Genetic Algorithm and Elman Network Used For Tuning The Parameters Of The PID Neural Controller Based Model Reference

Authors

• Ahmed Sabah Abdulameer, Control & Systems Engineering/University of Technology Baghdad, Iraq

Document Type

Original Study

Abstract

A neural network-based self-tuning PID controller is presented. The scheme of the controller is based on using a modified Elman recurrent neural network as a selftuner for (PID) controller. The proposed method has the advantage of not necessarily using a combined structure of identification and decision, common in a standard selftuning controller, because it uses a genetic algorithm based model reference. The paper explains the algorithm for a general case, and then presents a specific application on non-linear dynamical plant

How to Cite This Article

Abdulameer, Ahmed Sabah (2005) "Genetic Algorithm and Elman Network Used For Tuning The Parameters Of The PID Neural Controller Based Model Reference," Iraqi Journal of Computers, Communications, Control and Systems Engineering: Vol. 5: Iss. 1, Article 9.
Available at: https://ijccce.researchcommons.org/journal/vol5/iss1/9