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원격 제어 시스템에서의 신경망을 이용한 시간 지연 보상 제어기 설계

Design of a Time-delay Compensator Using Neural Network In a Tele-operation System

  • 최호진 (LIG 넥스원 연구원) ;
  • 정슬 (충남대학교 메카트로닉스공학과)
  • 투고 : 2011.07.14
  • 심사 : 2011.08.10
  • 발행 : 2011.08.25

초록

본 논문에서는 원격제어 시스템의 시간지연 문제를 분석하고 그 문제를 신경망으로 보상한다. 스미스 예측기는 시간지연 시스템에서 정확한 모델을 필요로 한다. 스미스 예측기의 모델링 오차를 보상하기 위해 신경회로망을 사용한다. 스미스 예측기를 구성하기 위해 Radial Basis Function(RBF) 신경회로망이 사용된다. 시뮬레이션과 실험을 통해 제안하는 방법의 동작을 검증한다.

In this paper, a time-delay problem of a tele-operated control system is investigated and compensated by neural network. The smith predictor requires an exact system model to deal with a time-delay in the system. To compensate for modeling errors in the configuration of the Smith predictor, a neural network approach is presented. Based on forming the Smith predictor structure, the radial basis function(RBF) neural network estimator is used. Simulation and experimental studies are conducted to show the functionality of the proposed method.

키워드

참고문헌

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피인용 문헌

  1. Robust teleoperation in a non-visible environment with a new prediction scheme vol.32, pp.2, 2018, https://doi.org/10.1007/s12206-018-0134-0