Combined Genetic Algorithm Control for Bearingless Motor Suspended System

Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 135)

Abstract

Genetic algorithm is an efficient global optimal searching algorithm. It is based on the natural selection and the heredity theory, and combined the principle of the fittest survival with the stochastic exchange of community internal chromosome. This paper takes bearingless motor as control object, makes the simulation in Matlab and use real-time emulation system dspace to experiment about the bearingless motor suspended system. The result demonstration that as increase iterative number of times the result parameter get more and more perfect to the suspension control. With the end of evolution, the algorithm finds the best control parameters. The algorithm is optimal globally, effect significantly to the suspension system, so it fitted for complex and non-linear bearingless motor about the suspension control.

Keywords

Genetic algorithm  Bearingless motor  Parameter optimization for the suspended system  Dspace  

Notes

Acknowledgments

This project founded by the priority academic program development of Jiangsu higher education institutions, national natural science foundation of China (61174055), natural science foundation of Jiangsu province (BK2008233) and research and innovation plan of university graduate in Jiangsu province(CXLX11_0583).

References

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Copyright information

© Springer Science+Business Media, LLC 2012

Authors and Affiliations

  1. 1.Department of Electrical and Information EngineeringJiangsu UniversityZhenjiangChina
  2. 2.Jiangsu Zhenjiang Installation GroupZhenjiangChina

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