Abordagens meta-heurísticas na sintonia de PID de ordem fracionária

Abstract

In most cases, careful tuning for conventional Proportional-Integral-Derivative (PID) controllers is used to get the highest performance for the widest range of applications. However, in more complex cases, such as multiple input and multiple output (MIMO) systems, fine-tuning methods do not extract the best behavior from the system. This performance can be improved using more advanced techniques, such as Fractional Order PID (FOPID), which is based on fractional calculus. Metaheuristic optimization techniques can be used to solve the problem of optimizing a PID controller. The goal of this paper is to assess the effectiveness of FOPID when it is tweaked using metaheuristics, including the Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Harris Hawks Optimization (HHO), Marine Predators Algorithm (MPA), and Manta Ray Foraging Optimization (MRO). The ball mill pulverizing system was utilized as a test technique to evaluate tuning performance. Over 50 different runs and statistical metrics of the fitness function were applied to assess the metaheuristics’ performance. At the end of this process, it became evident that the techniques are efficient in general, and the MPA was the metaheuristic with the smallest objective function values for structured tuning in the ball mill pulverizing system, making it the most efficient technique, while both classical techniques GA and PSO were the least efficient ones.