Advanced Control of Magnetic Levitation System via Black Widow Optimization and Fractional-order Techniques

Magnetic Levitation (MAGLEV) systems are inherently nonlinear, multivariable, and unstable, designed to levitate ferromagnetic objects without physical contact. These systems offer advantages such as reduced friction, minimal wear, and extended operational lifespan, making them ideal for various technical applications. To enhance their performance and achieve precise control, this study employs the Black Widow Optimization Algorithm (BWOA) to optimize Integer-Order PID (IOPID) and Fractional-Order PID (FOPID) controllers. Inspired by the mating behavior of black widow spiders, BWOA effectively tunes controller parameters by optimizing an objective function derived from the system’s characteristic equation. The results indicate that BWOA provides early convergence and superior fitness optimization compared to other algorithms. A comparative analysis of IOPID and FOPID controllers reveals that the FOPID controller exhibits superior performance due to its additional tunable parameters, resulting in improved system stability and control precision. This study underscores the potential of BWOA in advancing Magnetic Levitation technology by offering reliable, efficient, and high-performance levitation control solutions.