Fractional Modeling of the Speed of a DC Motor and Control with FOPID Controller

In this article, a new control strategy for a speed dc motor that is thought of as a black box is presented. The strategy involves identification with two models, the first is a traditional integer model and the second, which takes up more and more space in the identification part, is a fractional model. Modern heuristic techniques, like PSO, ABC, ACO, and GA, will be used in this phase of dentification Then comes a control phase with a fractional order proportional-integrator-derivative (FOPID) regulator. The FOPID controller is the most often used fractional order controller. The proportional gain K
p
, integral gain KI, derivative gain K
d
, integer order A, and derivative order
$u$
are the five parameters that make up the FOPID controller. To illustrate our strategy and the performance-based control effectiveness of the dc motor with a fractional model, we will apply the fractional regulator optimized by these algorithms on the two recognized models. Ordinary performance requirements specified by the corrector (overshoot, settling time, etc.) are executed while taking into account the Integral of Time and Absolute Error (ITAE) evaluation criteria. To show the effectiveness of our method, a robustness test with a variation of the parameters is carried out at the end of our work. A real-world DC motor's parameters are experimentally estimated using Matlab/Simulink connected to an Arduino Uno board. The proposed method proves that fractional calculus gives good performance for speed control of a DC motor.