Design of robust FOPI-FOPD controller for maglev system using particle swarm optimization - Yusif, Salwan Y.; Muhammd, Muhammad J. (Engineering and Technology Journal, 2021)
Magnetic Levitation System (MLS) is one of the benchmark laboratories models for designing and testing feedback control systems in the presence of the parametric uncertainties and disturbances effect. Therefore, the MLS can be regarded as a tool to study and verify a certain robust controller design. In this paper, two types of powerful control schemes are presented to control the MLS. The first controller is a robust PI-PD controller, while the other is a robust fractional order FOPI-FOPD controller which provides two extra degrees of freedom to the system. In both controller design procedures, the Particle Swarm Optimization (PSO) algorithm is used to find the best values of controller parameters subject to the time-domain objective function and H∞ constraints. All modeling processes including parameterization, optimization, and validation of the controllers are performed using MATLAB. The simulation results show that the MLS with robust FOPI-FOPD is faster and more stable than the MLS with robust classical PI-PD. Also, the proposed FOPI-FOPD controller gives far superior results than the PI-PD controller for disturbance is one of the benchmark laboratories models for designing and testing feedback control systems in the presence of the parametric uncertainties and disturbances effect. Therefore, the MLS can be regarded as a tool to study and verify a certain robust controller design. In this paper, two types of powerful control schemes are presented to control the MLS. The first controller is a robust PI-PD controller, while the other is a robust fractional order FOPI-FOPD controller which provides two extra degrees of freedom to the system. In both controller design procedures, the Particle Swarm Optimization (PSO) algorithm is used to find the best values of controller parameters subject to the time-domain objective function and H∞ constraints. All modeling processes including parameterization, optimization, and validation of the controllers are performed using MATLAB. The simulation results show that the MLS with robust FOPI-FOPD is faster and more stable than the MLS with robust classical PI-PD. Also, the proposed FOPI-FOPD controller gives far superior results than the PI-PD controller for disturbance rejection.