Magnetic Levitation System Control and Multi-Objective Optimization Using Golden Jackal Optimization

Based on single objective Golden Jackal Optimization (GJO), this paper proposes multi-objective GJO to address the flaws of magnetic levitation system fractional-order controllers with various design parameters and challenging debugging. The algorithm calculates the position of male and female Golden Jackals based on diversity and rapidity by evaluating the stage of iteration times and employing the corresponding evaluation technique, and extending the position update equation by introducing the individual's history experience to effectively alter update strategies for the initial algorithm. Then, it is used in the magnetic levitation fractional order control system, and obtains a good control effect, which provides an effective guarantee for the parameter setting method.