Robust controller design for single axis magnetic levitation system.

This paper demonstrates theoretically the main idea of magnetic force control in magnetic levitation system using flux density measurements. A Hall-effect sensor is used to sense the flux density in the air gap. The magnetic force is obtained by its proportional relation to the flux density. A simple magnetic levitation system which consists of a U-shaped electromagnet and a manipulator is used. First, the system dynamics are described in state space form using air gap displacement, velocity of the magnetically levitated manipulator, and the flux density as state variables. Second, the magnetic force regulated using Hf controller to achieve robust stability, disturbance/noise rejection and asymptotic tracking. Simulation results in terms of speed and accuracy are presented

H_infinity controller design to control the single axis magnetic levitation system with parametric uncertainty

In this study the force control design of single axis magnetic levitation system using H_infinity controller is presented. First, the system dynamics are linearized and described in transfer function form. Second, the magnetic force is regulated using H_infinity controller to achieve robust stability, disturbance/noise rejection and asymptotic tracking. A multiplicative unstructured model extracted from the parametric uncertainty is used for H_infinity control design. The obtained results showed that robust stability and performance have been achieved. On the other hand, an improved and more reliable time response compared with previous work also has been achieved in this study

Design of robust particle swarm optimization - tuned fuzzy controller for a Single Axis Small Magnetic Levitation System

A control system is robust when it has low sensitivity, it is stable over the range of parameter variations and the performance continues to meet the specification in the presence of a set of changes in the system parameters and disturbances. In this work the design of the robust linear and nonlinear controllers for Single Axis Magnetic Levitation System are presented. These controllers must overcome the problems of the high steady state error and robustness in the magnetic levitation system. The design of H∞ robust controller is presented first and the system dynamics are linearized to be suitable for applying the H∞ robust control technique. The magnetic force is regulated using this controller to achieve robust stability and performance, disturbance/noise rejection and asymptotic tracking with zero steady state error. The plant with structured uncertainty is expressed in terms of unstructured multiplicative uncertainty to cover the overall change in system parameters. The unstructured multiplicative uncertainty is determined using curve fitting method. The designed H∞ controller has assured robust stability and robust performance of the single axis magnetic levitation system with parametric uncertainty. The parameters of the performance and control weighting functions that are obtained using trial and error lead to obtain a robust controller that achieves force control of magnetic levitation system. The design of PD like fuzzy robust controller is presented secondly in this work. The Particle Swarm Optimization method (PSO) is used to find the optimal values of the Scalar gains and the membership functions subject to the robust control and minimum error constraints. The designed PD like fuzzy controller has assured robust stability and robust performance of the nonlinear model of single axis magnetic levitation system. This controller minimizes the rules from 64 rules to 16 rules and achieved zero steady state error without using the integral. Finally, a comparison between the performances of the H∞ controller and the optimal fuzzy logic controller has been made. It shows that the nonlinear optimal fuzzy logic controller achieve better performance than the linear H∞ controller

Design of PSO-based Fuzzy Logic Controller for single Axis Magnetic Levitation System.

In this paper, a particle swarm optimization (PSO) method is proposed to design an optimal robust fuzzy logic controller (FLC). The objective of this paper is to design a nonlinear optimal robust controller for the single axis magnetic levitation system with high accuracy. PSO algorithm is applied to search globally optimal parameters of FLCs. Three different FLCs are designed. First, proportional derivative (PD)-like FLC. Second, the FLC is based on the PSO algorithm to find the optimal range of the eight linguistic membership functions (FLC1 with PSO algorithm). Finally, the FLC is based on the PSO algorithm to find the optimal range and shape of the four linguistic membership functions (FLC2 with PSO algorithm). The performances of three different FLCs are compared. Simulation results show that PSO-based optimal FLCs find the optimal range and shape of the four linguistic membership functions and achieved better performance than the other proposed controllers, minimizing 48 fuzzy rules. © 2011 Institute of Electrical Engineers of Japan