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An Experimental Study on Realtime Estimation of a Nominal Model for a Disturbance Observer: Recursive Least Squares Approach

실시간 공칭 모델 추정 외란관측기에 관한 실험 연구: 재귀최소자승법

  • Lee, Sang-Deok (ISEE, Department of Mechatronics Engineering, Chungnam National University) ;
  • Jung, Seul (ISEE, Department of Mechatronics Engineering, Chungnam National University)
  • 이상덕 (충남대학교 메카트로닉스공학과) ;
  • 정슬 (충남대학교 메카트로닉스공학과)
  • Received : 2016.04.01
  • Accepted : 2016.06.24
  • Published : 2016.08.01

Abstract

In this paper, a novel RLS-based DOB (Recursive Least Squares Disturbance Observer) scheme is proposed to improve the performance of DOB for nominal model identification. A nominal model can be generally assumed to be a second order system in the form of a proper transfer function of an ARMA (Autoregressive Moving Average) model. The RLS algorithm for the model identification is proposed in association with DOB. Experimental studies of the balancing control of a one-wheel robot are conducted to demonstrate the feasibility of the proposed method. The performances between the conventional DOB scheme and the proposed scheme are compared.

Keywords

References

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