Multi-Objective Optimization of the Electromagnetic Actuator Control

Sebastian Pecolt; Tomasz Krzyżyński

doi:10.4028/www.scientific.net/SSP.198.553

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HomeSolid State PhenomenaSolid State Phenomena Vol. 198Multi-Objective Optimization of the...

Multi-Objective Optimization of the Electromagnetic Actuator Control

Abstract:

This paper presents the linear electromagnetic motor (LEM) which consists of two solenoids and a slide control with neodymium magnet bars placed on its end. The work of the electromagnetic motor is based on the phenomenon of electromagnetic repulsion. The device also includes an electromagnetic brake which allows to stop the slider or to hold the slider in a fixed position, without electricity supply. The range of the slider movement is up to 50mm. The paper deals with the problem of implementation of the Genetic Algorithm GA to calculate Pareto-optimal solutions. In this process, the functions of voltage powering solenoids used to control the position of the linear electromagnetic motor are evaluated. This procedure assumes minimizing two conflicted criteria: the time of movement of the motor and the energy input. In this case the device works in the open-loop system without a feedback loop. The results of the application of the conventional PID controller are also presented, which allows precision positioning up to 1µm. The experimental results are compared with Matlab-Simulink simulations.

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Periodical:

Solid State Phenomena (Volume 198)

Pages:

553-558

DOI:

https://doi.org/10.4028/www.scientific.net/SSP.198.553

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Online since:

March 2013

Authors:

Sebastian Pecolt, Tomasz Krzyżyński

Keywords:

Control, Electromagnetic Brake, Electromagnetic Motor, Genetic Algorithm (GA), Optimization

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References

[1] Popov A.: Genetic Algorithms For Optimization, Programs for MATLAB Version 1. 0 User manual, Hamburg, (2005).

Google Scholar

[2] Ansys Ansoft Maxwell 3D v12 User Guide, (2010).

Google Scholar

[3] Pecolt S.: Selected issues of the construction and optimization of the control of a positioning device with an electromagnetic system, PhD thesis, Koszalin Technical University, Koszalin (2012).

Google Scholar

[4] Błażejewski A., Krzyżyński T.: Multi-objective optimization using genetic algorithm in room acoustics, Transcomp - XIV International Conference, Computer Systems Aided Science, Industry and Transport, (2011).

Google Scholar

[5] Jingsyan T., Kuang-Chao F., Tien-Fu L.: A Genetic Approach on the PID Control of VCM for Auto-focusing Laser Probe. Materials Science Forum Vols. Tarns Tech Publications, Switzerland (2006).

DOI: 10.4028/www.scientific.net/msf.505-507.373

Google Scholar

[6] Tarnowski W.: Poli-optimization of Nonlinear Processes,. PAK vol. 53, nr 8/(2007).

Google Scholar