Design of a state feedback controller for the stabilization of a magnetic levitation system considering a nonlinear second-order dynamic model

Authors

  • Carlos Andres Vergara-Espitia Universidad Distrital Francisco Jose de Caldas, , Bogota D.C., 110121, Colombia
  • Johan Sebastian Sanchez-Rodriguez Universidad Distrital Francisco Jose de Caldas, , Bogota D.C., 110121, Colombia
  • Oscar Danilo Montoya Giraldo Universidad Distrital Francisco Jose de Caldas, , Bogota D.C., 110121, Colombia https://orcid.org/0000-0001-6051-4925

DOI:

https://doi.org/10.19139/soic-2310-5070-3747

Keywords:

Magnetic levitation system, state-feedback controller, second-order dynamic model, linear control

Abstract

This paper addresses the stabilization and reference tracking problems in a magnetic levitation system, characterized by its inherent nonlinearity and open-loop instability. A second-order dynamic model of the system is derived, considering the injected current as the control input. An exact linearization procedure based on error dynamics is employed to obtain an equivalent linear representation. From this model, two state-feedback control strategies are developed: a conventional approach and an extended formulation that incorporates integral action to ensure accurate tracking of the reference position. The performance of the proposed schemes is evaluated against a decoupled nonlinear proportional–integral controller using metrics related to stability, transient response, and control effort. The results demonstrate the structural advantages of the state-space-based approach, highlighting its systematic capability to meet dynamic specifications while improving closed-loop behavior under disturbances and parametric variations.

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Published

2026-07-15

How to Cite

Vergara-Espitia, C. A., Sanchez-Rodriguez, J. S., & Montoya Giraldo, O. D. (2026). Design of a state feedback controller for the stabilization of a magnetic levitation system considering a nonlinear second-order dynamic model. Statistics, Optimization & Information Computing. https://doi.org/10.19139/soic-2310-5070-3747

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Section

Research Articles

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