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Comparison of controllers and mathematical modeling of a magnetic levitator

Abstract:

This work presents the mathematical modeling and simulation of a magnetic levitator, and a comparison of different control techniques, applied on the system, in order to visualize which technique better stabilizes the magnetic levitator. The dynamical modeling was done applying the Newton Euler’s formulation, and the obtained equations were represented on the space state. Then the system was linearized applying Taylor’s approximation, and the obtained matrixes were used for the controller’s design. The employed controllers for the comparison were: Feedback Controller, Linear–quadratic regulator (LQR), and the neural-network based nonlinear autoregressive moving average controller (NARMA). Finally, the designed controllers and the plant were tested under several simulations using MATLAB and Symulink. The results proved that the three techniques were capable of stabilizing this particular system, and some significant advantages were found applying the NARMA and LQR techniques.