MODELING AND CONTROLLER DESIGN OF A MAGNETIC
LEVITATION SYSTEM WITH FIVE DEGREES OF FREEDOM
E. Alvarez-Sanchez, Ja. Alvarez-Gallegos and R. Castro-Linares
CINVESTAV-IPN, Department of Electrical Engineering
Av. IPN No. 2508, Col. San Pedro Zacatenco
07360 Mexico, D.F., Mexico
Keywords:
Nonlinear system, modeling, control, maglev.
Abstract:
In this paper, the nonlinear mathematical model with five DOFs (degrees-of-freedom) of a magnetic levitation
system is developed and analyzed. Then a second order sliding mode controller is proposed to regulate the
levitation to a desired position, stabilizethe other 4 DOFs in the nonlinear system and compensate the unknown
increments on the load. Simulation results are presented to show the effectiveness of the proposed controller.
1 INTRODUCTION
The transport of material or products is a major prob-
lem in the manufacturing automation industry. As
it currently stands transport specifications can be so
variable from process within a single plant that each
operation might require its own transport. Using mag-
netic levitation (maglev), a carrier can be partially or
totally levitated or suspended by magnetic fields gen-
erated along the guiding tracks. This allows the car-
rier to move with little or no contact to the guiding
tracks, thus greatly minimizing the problems of en-
vironmental contamination. Of course, such contact-
free levitation has to be enforced for all DOFs of the
rigid body.
Maglev systems offer many advantages such as
frictionless, low noise, the ability to operate in high
vacuum environments and so on. Previous works in
this area span many fields. Some well known fields
include maglev transportation (Luguang, 2002), mi-
crorobotics (Khamesse et al., 2002), photolitography
(Kim and Trumper, 1998), positioning (Suk and Baek,
2002), launch systems (Jacobs, 2001) and so on.
In general a maglev system can be classified, based
on the levitation forces, as an attractive system or a
repulsive one, each type having various kinds of pos-
sible arrangements. Most of the maglev systems dis-
cussed in the literature are attractive, where attrac-
tive forces are applied between the moving carriage
0
Research partially supported by CONACYT under
Grant 44969 and by CINVESTAV
and fixed guide tracks. On the other hand, the repul-
sive maglev systems use repulsive forces to push the
moving carriage above the fixed guide tracks. How-
ever, a magnetic levitation system is highly nonlinear
and unstable, and a feedback control is necessary to
achieve a stable operation. Many works have devel-
oped linear controllers, and the control laws have been
based on traditional control methods and only local
stability is guaranteed. These developed controllers
may not meet the precision control purpose for ma-
glev systems, because these systems are naturally un-
der the influence of many uncertainties. On the other
hand, the works that use nonlinear mathematical mod-
els (Kaloust et al., 2004) only control 2 DOFs and
consider the other DOFs stables.
To overcome this problem, a new approach called
“second order sliding mode (SOSM)” has been pro-
posed (Elmali and Olgac, 1992; Bartolini et al., 2001;
Castro-Linares et al., 2004). This approach has the
main advantages of the standard sliding mode con-
trol technique, the chattering effect is eliminated and
a high order precision is provided.
In this paper the kind of maglev system is a repul-
sive one, using an arrangement of a permanent mag-
net levitated above an electromagnet. The control de-
sign proposed here is based on SOSM control tech-
nique for the nonlinear maglev mathematical model;
this controller is robust when different loads are put
on the carrier and guarantees stabilization and preci-
sion positioning.
The organization of this paper is as follows. In sec-
tion II, the maglev system is described, some magnet-
99
Alvarez-Sanchez E., Alvarez-Gallegos J. and Castro-Linares R. (2005).
MODELING AND CONTROLLER DESIGN OF A MAGNETIC LEVITATION SYSTEM WITH FIVE DEGREES OF FREEDOM.
In Proceedings of the Second International Conference on Informatics in Control, Automation and Robotics - Signal Processing, Systems Modeling and
Control, pages 99-106
DOI: 10.5220/0001184100990106
Copyright
c
SciTePress