Monday, February 8, 2010

Magnetic Levitation System Control

Design of a Robust Controller for a Magnetic Levitation System
A Magnetic Levitation System (Maglev) is considered as a good test-bed for the design and analysis of control systems since it is a nonlinear unstable plant with practical uses in high-speed transportation and magnetic bearings. The objective of this project is to design a robust controller and implement it on a test-bed to help students learn the robust control design. In this project a robust controller for a maglev system is designed, using H-infinity optimization [3]. Complete mathematical models of the electrical, mechanical and magnetic systems are also developed. The design and simulations are performed under a Matlab/Simulink platform. Wincon control software of Quanser Inc. [7] is used to establish the link between the Matlab/Simulink models and the actual magnetic levitation system.

Design and Implementation of a Controller for a
Magnetic Levitation System
This paper reports on the design of a controller for keeping a steel ball suspended in the air. In
the ideal situation, the magnetic force produced by current from an electromagnet will counteract the weight of the steel ball. Nevertheless, the fixed electromagnetic force is very sensitive, and there is noise that creates acceleration forces on the steel ball, causing the ball to move into the unbalanced region. The main function of this controller is to maintain the balance between the magnetic force and the ball’s weight. According to the analytical method, the mathematical models of this magnetic levitation system were established with the goal of designing the control system. System linearization and phaselead compensation were employed to design the controller of this unstable nonlinear system. The algorithm
proposed in this paper provides a robust closed-loop magnetic levitation system which can stabilize the system over a large range of variations of the suspended mass. The design methods of this system are presented in this paper. And lastly, the hardware is implemented for a scientific demonstration.

This paper concerns the application of a predictive control methodology to the stabilization and referencefollowing operation of a magnetic levitation process. From a control engineering point of view, the problem is challenging owing to the nonlinear and unstable nature of the plant, the required positioning accuracy and the operational restrictions on the manipulated and controlled variables during transients.

The formulation employed in this work is based on a linear prediction model obtained by linearizing the plant dynamics around the center of the working range of the position sensor.
Offset-free tracking is achieved by augmenting the cost function with a term associated to the integral of the tracking error. Operational constraints on the input (current in the electromagnet coil) and output (width of the air gap between the electromagnet core and the suspended object) of the process are enforced in the optimization process. The optimal control sequence is implemented in a receding-horizon strategy, in which the optimization is repeated at every sampling instant, by taking into account the new sensor readings. The design and validation of the predictive control loop are carried out
by using physical parameters from a real magnetic levitation process. The results obtained by simulation show that the explicit treatment of operational constraints, especially those related to the input variation rate, is fundamental to an appropriate control of the system.

This paper deals with the magnetic levitation control system of a metallic
sphere, which is an interesting and visually impressive equipment for demonstrating
many intricate problems. In order to stimulate future research, after short description
of the system operation in analogue and digital mode, several open problems in areas
of electrical and control engineering are offered. Also, the paper presents some initial
outcomes in creating a laboratory environment for remote monitoring of the magnetic
levitation equipment.

Modeling and Control of a Magnetic Levitation System
Magnetic levitation technology has been receiving increasing attention
because it helps eliminate frictional losses due to mechanical contact. Some
engineering applications include high-speed maglev trains, magnetic bearings and
high-precision platforms. The objectives of this project are to model and control a
laboratory-scale magnetic levitation system. The control algorithm is
implemented using assembly language on Intel 8051 microprocessor to levitate
and stabilize a spherical steel ball at a desired vertical position.

Inverse Model Based Adaptive Control of Magnetic Levitation System
This paper presents, an adaptive finite impulse response
(FIR) filter based controller used for the tracking
of a ferric ball under the influence of magnetic
force. The adaptive filer is designed online as approximate
inverse system. To stabilize the open-loop unstable
and highly nonlinear magnetic levitation system,
PID controller is designed using polynomial approach.
To improve the stability, an adaptive FIR filter
is added along side the PID controller while the
use of the proposed controller has improved tracking.
Since adaptive FIR filters are inherently stable so the
controller remains stable. Experimental results are included
to highlight the excellent position tracking performance.

AFIR addition to improve the stability


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