The Transactions of The Korean Institute of Electrical Engineers (전기학회논문지)

The Korean Institute of Electrical Engineers (대한전기학회)
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Experimental Study on a Monte Carlo-based Recursive Least Square Method for System Identification

몬테카를로 기반 재귀최소자승법에 의한 시스템 인식 실험 연구

  • Lee, Sang-Deok (Dept. of Mechatronics Engineering, Chungnam National University) ;
  • Jung, Seul (Dept. of Mechatronics Engineering, Chungnam National University)
  • Received : 2017.06.19
  • Accepted : 2018.01.23
  • Published : 2018.02.01
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Abstract

In this paper, a Monte Carlo-based Recursive Least Square(MC-RLS) method is presented to directly identify the inverse model of the dynamical system. Although a RLS method has been used for the identification based on the deterministic data in the closed loop controlled form, it would be better for RLS to identify the model with random data. In addition, the inverse model obtained by inverting the identified forward model may not work properly. Therefore, MC-RLS can be used for the inverse model identification without proceeding a numerical inversion of an identified forward model. The performance of the proposed method is verified through experimental studies on a control moment gyroscope.

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References

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