• 제목/요약/키워드: 적응 피이드포워드 제어

검색결과 6건 처리시간 0.018초

주기적 외란을 제거하기 위한 효율적인 적응제어기 (A Novel Adaptive Controller for Periodic Disturbances Rejection)

  • 나희승;박영진
    • 한국소음진동공학회:학술대회논문집
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    • 한국소음진동공학회 1994년도 춘계학술대회논문집; 영남대학교, 20 May 1994
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    • pp.22-27
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    • 1994
  • 본 논문의 목적은 피이드백 제어시스템에서 주기적 외란(periodic disturbances),d$_{\omega}$, 이 출력센서에 감지될 경우, 이를 제거하기 위한 새로운 적응제어기(adaptive controller)를 설계하는 것이다. 2장에서는 주기적 외란을 제거하기 위한 방법으로 많이 사용되어 온 피이드백 제어기 (feedback controller)와 피이드포워드 제어기 (feedforward controller)를 설명한다. 3장에서는 적응 피이드포워드 제어기가 페루프 전달함수를 변경시키는 점에서 피이드백 제어기와 동일함을 보이고, 전달함수를 변경시키지 않아 페루프시스템의 강건성을 저하시키지 않는 효율적인 피이드포워드 제어기를 설계한다. 4장에서는 제안된 피이드포워드 제어기의 학습알고리즘을 유도한다. 5장에서는 모의 실험을 통하여 제안한 피이드포워드 제어기 및 학습 알고리즘의 효율성을 검증하기로 한다.

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자기베어링지지 연삭기 추축계의 고속 회전시 런아웃 적응제어 (Adaptive Runout Control of Magnetically Suspended High Speed Grinder Spindle)

  • 노승국;경진호;박종권;최언돈
    • 한국정밀공학회:학술대회논문집
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    • 한국정밀공학회 1997년도 추계학술대회 논문집
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    • pp.52-55
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    • 1997
  • In this paper, the case study of reducing rotational errors is done for a grinding spindle with an active magnetic bearing system. The rotational errors acting on the magnetic bearing spindle are due to mass unbalance of rotor, runout, grinding excitation and unmodeled nonlinear dynamics of electromagnets. For the most case, the electrical runout of sensor target is big even in well-finished surface; this runout can cause a rotation error amplified by feedback control system. The adaptive feedforward method based on LMS algorithm is discussed to compensate this kind of runout effects, and investigated its effectiveness by numerical simulation and experimental analysis. The rotor orbit size in both bearings is reduced about to 5 pin due to lX rejection by feedforward control up to 50, 000 rpm.

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저주파 순음소음저감을 위한 능동 순음 소음제어 (Active Tonal Noise Control to Reduce the Low Frequency Tonal Sound)

  • 나희승;박영진
    • 소음진동
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    • 제8권6호
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    • pp.1037-1042
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    • 1998
  • This paper discusses the dependence of the convergence rate on the acoustic error path in these popular algorithms and introduces new algorithms which increase the convergence region regardless of the time-delay in the acoustic error path. We also Propose a novel control algorithm (AFC/CAFC) for tonal noise cancellation. The proposed algorithm estimates the magnitude and phase of the tonal noise. The algorithm uses the steepest descent method for the phase/magnitude estimation. Performances of tile CAFC algorithm are presented in comparison with those by the AFC algorithm based on computer simulations and experiments.

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자기베어링으로 지지된 연삭 스핀들의 런아웃 제어 (Runout Control of a Magnetically Suspended Grinding Spindle)

  • 노승국;경진호;박종권;최언돈
    • 한국정밀공학회:학술대회논문집
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    • 한국정밀공학회 2000년도 춘계학술대회 논문집
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    • pp.1011-1015
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    • 2000
  • In this paper, the case studies of reducing rotational errors is theoretically done for a grinding spindle with an active magnetic bearing system. The rotational errors acting on the magnetic bearing spindle are due to mass unbalance of rotor, runout, grinding excitation and unmodeled nonlinear dynamics of electromagnets. The adaptive feedforward method based on LMS algorithm is discussed to compensate output and input disturbances, and investigated its effectiveness by numerical simulation. The feedforward control reduced external excitation and rotational error for specified frequency. The interpolation method using impulse function for cancelling the electrical 'uncut is studied. These methods show their effectiveness for the rotational accuracy of the improving magnetic bearing spindle through some simulation results of the rotational error decreased by them.

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적응 Feedforward를 이용한 자기베어링 고속 주축계의 전기적 런아웃 제어 (Runout Control of a Magnetically Suspended High Speed Spindle Using Adaptive Feedforward Method)

  • 노승국;경진호;박종권
    • 한국정밀공학회지
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    • 제19권12호
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    • pp.57-63
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    • 2002
  • In this paper, the feedforward control with least mean square (LMS) adaptive algorithm is proposed and examined to reduce rotating error by runout of an active magnetic bearing system. Using eddy-current type gap sensor fur control, the electrical runout caused by non-uniform material properties of sensor target produces rotational error amplified in feedback control loop, so this runout should be eliminated to increase rotating accuracy. The adaptive feedforward controller is designed and examined its tracking and stability performances numerically with established frequency response function. The tested grinding spindle system is manufactured with a 5.5 ㎾ internal motor and 5-axis active magnetic bearing system including 5 eddy current gap sensors which have approximately 15 ~ 30 ${\mu}{\textrm}{m}$ of electrical runout. According to the experimental analysis, the error signal in radial bearings is reduced to less than 5 ${\mu}{\textrm}{m}$ when it is rotating up to 50,000 rpm due to applying the feedforward control for first order harmonic frequency, and vibration of the spindle base is also reduced about same frequency.

자기베어링으로 지지된 연삭 스핀들의 런아웃 제어 -LMS Feedforward 제어를 이용한 실험적 해석- (Runout Control of Mgenetically Suspended Grinding Spindle - Experimental Analysis of Adaptive LMS Feedforward Control Method -)

  • 노승국;경진호;박종권;최언돈
    • 한국정밀공학회:학술대회논문집
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    • 한국정밀공학회 2000년도 추계학술대회 논문집
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    • pp.997-1001
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    • 2000
  • In this paper, the case studies of reducing rotational errors is theoretically done for a grinding spindle with an active magnetic bearing system. The rotational errors acting on the magnetic bearing spindle are due to mass unbalance of rotor, runout, grinding excitation and unmodeled nonlinear dynamics of electromagnets. For the most case, the electrical runout of sensor target is big even in well finished surface, this runout can cause a rotation error amplified by feedback control system. The adaptiveed forward method based on LMS algorithm is discussed to compensate this kind of runout effects, and investigated its effectiveness by numerical simulation and experimental analysis. The electrical runout form the rear sensor target of grind spindle is about 70$\mu\textrm{m}$ with harmonic frequencies. The rotor orbit size in rear bearing is reduced about to 5$\mu\textrm{m}$ due to 1X and 2X rejection by feedforward control.

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