Modelling and Simulation of LQR and LFSV Controllers in the Magnetic Levitation System (MLS)

Alvaro Romero Acero
Julian Andrés Orozco Quiceno
Jovani Alberto Jiménez Bulies



In this article a control analysis in state variables is presented, applied to the nonlinear Magnetic Levitation system (MLS), which consists in keeping objects suspended in the air without any mechanical contact through the interaction of magnetic force. The design of Linear Quadratic Regulator (LQR) and Linear Feedback in State Variables (LFSV) controllers is implemented with the aim of comparing the results which guarantee a better stability performance in the system. The mathematical representation of the nonlinear and linearized model of the MLS plant is examined through the design of algorithms and simulation in Simulink-Matlad. In this way, the behavior of the system when there are perturbations and input changes is contrasted, with the priority of exerting a low control action as parameter of the system to be optimized.

Palabras clave

Linearization, Stability, State observer, Controllers LQR and LSFV

Texto completo:



S. Kumar, R. Singh, "Nonlinear Control of a Magnetic Levitation System using Feedback Linearization," Advanced Communication Control and Computing Technologies (ICACCCT), 2014 International Conference on., 152-156, 2014.

R. Morales, V. Feliu, H. Sira-Ramírez, "Nonlinear Control for Magnetic Levitation Systems Based on Fast Online Algebraic Identification of the Input Gain," Control Systems Technology, IEEE Transactions on., 19(4), 757-771, 2011.

P. Suster, A. Jadlovska, "Modeling and control design of Magnetic levitation system," Applied Machine Intelligence and Informatics (SAMI), 2012 IEEE 10th International Symposium on., 295-299, 2012.

E. Kofman, F. Fontenla, H. Haimovich, M. Seron, “Control design with guaranteed ultimate bound for feedback linearizable systems,” Proceedings of the 17th World Congress The International Federation of Automatic Control Seoul, Korea, 242-247, 2008.

P. Suster and A. Jadlovska, "Modeling and Control Design of Magnetic Levitation System," Applied Machine Intelligence and Informatics (SAMI), 2012 IEEE 10th International Symposium on., 295-299, 2012.

R. Uswarman, A. Cahyadi, O. Wahyunggoro, "Control of a magnetic levitation system using feedback linearization," Computer, Control, Informatics and Its Applications (IC3INA), 2013 International Conference on., 95-98, 2013.

M. Seron, (2001) Nonlinear Systems - Laboratory of Dynamical Systems and Signal Processing (LSD), [Internet], National University of Rosario. Disponible desde: [Acceso 1 de agosto 2014].

R. Dorf, R. Bishop, "Modelos en variables de estado". En: Sistemas de Control Moderno, ed.; Prentice Hall, New Jersey, p.79–129.

P. Shiakolas, S.Van-Schenck, D. Piyabongkarn, I. Frangeskou, "Magnetic levitation hardware-in-the-loop and MATLAB-based experiments for reinforcement of neural network control concepts," Education, IEEE Transactions on., 47(1), 33-41, 2004.

T. Kumar, S. Shimi, D. Karanjkar, S. Rana, "Modeling, simulation and control of single actuator magnetic levitation system," Engineering and Computational Sciences (RAECS), 2014 Recent Advances in., 1-6, 2014.

K. Ogata, Modern control engineering 5th edition. Upper Saddle River, New Jersey: Prentice Hall, 2010, pp. 912.

Oishi, (2010) State Feedback - Ackermann’s Formula, [Internet], University of British Columbia. Disponible desde: [Acceso 1 de junio 2015].

E. Kumar, J. Jerome, K. Srikanth, "Algebraic approach for selecting the weighting matrices of linear quadratic regulator," Green Computing Communication and Electrical Engineering (ICGCCEE), 2014 International Conference on., 1-6, 2014.

A. Romero, A. Marín, A. Jiménez, “Modelado, simulación e implementación de controladores LQR y RLVE al sistema péndulo invertido rotacional usando la plataforma NI ELVIS II,” Revista Científica Guillermo de Ockham, 11(1), 67-78, 2013.

P. Yadav, R. Mitra, "Real time implementation of hybrid fuzzy logic controller with linear quadratic regulator on magnetic levitation," Computational Intelligence and Computing Research (ICCIC), 2013 IEEE International Conference on., 1-4, 2013.

C. Chen, Linear system theory and design 4th edition. Oxford University Press, 2012, pp. 400.

Enlaces refback

  • No hay ningún enlace refback.

Licencia Creative Commons
Este trabajo esta licenciado bajo una Licencia Internacional Creative Commons Atribución-NoComercial-SinDerivados 4.0.


ISSN : 1692-8261 Versión impresión
ISSN : 2216-1368 Versión Web

RedesRepositorio UACRedes Sociales

Licenciada bajo: