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Fractional PID Position Control Tuned by Bio-Heuristics on an ARM Platform

Abstract:

Today, modern applications in the field of industrial control have forced many traditional controls to evolve in order to optimize their industrial processes, which is why this study shows the implementation of a fractional order PID control oriented to the speed of a permanent magnet DC motor. It uses bio-heuristic optimization methods for parameter tuning, and its performance will be compared with an entire order PID control tuned by Euler’s MATLAB software. Unlike the traditional PID control, the fractional PID control to be developed has two additional design parameters that allow a better performance of the system. Moreover, by including bio-inspired optimization techniques such as Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO), it is possible to obtain an optimal response of its parameters, compared to classical methods. On the other hand, for the simulation of the control loop, the software MATLAB/SIMULINK and the microcontroller STM32F407 with Advanced Risk Machine (ARM) technology is used, with which the reading and processing of data is obtained. In order to validate the development of the control carried out, the Integral Time Absolute Error (ITAE) is used, which is a performance index that together with the Wilcoxon method allows to compare the controls carried out. At the end of the paper, the results, the robustness of the control and its viability are shown.