Journal of Institute of Control, Robotics and Systems (제어로봇시스템학회논문지)

Institute of Control, Robotics and Systems (제어로봇시스템학회)
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Error elimination for systems with periodic disturbances using adaptive neural-network technique

주기적 외란을 수반하는 시스템의 적응 신경망 회로 기법에 의한 오차 제거

  • Kim, Han-Joong (Korea Inspection & Engineering Co.Ltd) ;
  • Park, Jong-Koo (Dept.of Electric Electronics Computer Engineering, Sungkyunkwan University)
  • 김한중 (대한검사기술 주식회사 부설연구소 연구원) ;
  • 박종구 (성균관대학교 전기전자 및 컴퓨터공학부)
  • Published : 1999.11.01
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Abstract

A control structure is introduced for the purpose of rejecting periodic (or repetitive) disturbances on a tracking system. The objective of the proposed structure is to drive the output of the system to the reference input that will result in perfect following without any changing the inner configuration of the system. The structure includes an adaptation block which learns the dynamics of the periodic disturbance and forces the interferences, caused by disturbances, on the output of the system to be reduced. Since the control structure acquires the dynamics of the disturbance by on-line adaptation, it is possible to generate control signals that reject any slowly varying time-periodic disturbance provided that its amplitude is bounded. The artificial neural network is adopted as the adaptation block. The adaptation is done at an on-line process. For this , the real-time recurrent learning (RTRL) algoritnm is applied to the training of the artificial neural network.

Keywords

References

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