Genetic algorithm and Elman network used for tuning the parameters of the PID neural controller based model reference

Abstract EN

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.