Robust 2-DOF FOPID Controller Design for Maglev System Using Jaya Algorithm

Abstract

In this paper, 1-Degree of Freedom (1-DOF) and 2-Degree of Freedom (2-DOF) Integer Order (IO) and Fractional Order (FO) Proportional–Integral–Derivative (PID) Controller has been designed for the Magnetic Levitation (Maglev) system. Maglev is one of the most versatile research-oriented laboratory instruments in the field of control systems engineering. The controller for the Maglev system is designed in such a way that a ferromagnetic ball can precisely levitate in a controlled electromagnetic field with particular design specifications. The controller parameters can be appropriately identified by optimizing the objective function with various popular artificial intelligence based evolutionary optimization algorithms. The 2-DOF controller structure takes care of both reference signal tracking and disturbance rejection through the feedback path. The 1 and 2-DOF controller structures with both Integer as well as Fractional Order approaches for different nonlinear systems were already discussed in various papers. However, the application of the Fractional Order control technique on a highly nonlinear Maglev system using the Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Hybrid Particle Swarm Optimization (Hybrid PSO), and recently developed Jaya Algorithm is of our interest. Observation of the final analysis based on different simulation results states that as the controller structure moves from 1-DOF to 2-DOF, the performance of the system and the control signal gets improved. The robustness analysis has also been incorporated in this study which shows that the 1 and 2-DOF IOPID and FOPID controllers designed using different optimization algorithms for the Maglev plant are robust in nature.