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      KCI등재 SCIE SCOPUS

      Practical Implementation of a Factorized All Pass Filtering Technique for Non-minimum Phase Models

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      https://www.riss.kr/link?id=A106053622

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      다국어 초록 (Multilingual Abstract)

      One of the problems of the inverse model-based control techniques is the stability of the identified inverse model after the estimation process by the recursive least square (RLS) method. One solution is to use the all pass filtering (APF) technique to transform non-minimum phase models into minimum phase models [9]. However, there are several cases not cured by the all pass filtering method when the all pass filter algorithm is implemented on the hardware. In this paper, an improved version of the all pass filtering technique is presented to deal with the non-minimum phase models. The factorized APF (fAPF) technique for non-minimum phase models is presented to suggest a simple solution. A simple method for avoiding the calculation of complex numbers is also presented for the easy implementation. Several examples are given to support the proposal.
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      One of the problems of the inverse model-based control techniques is the stability of the identified inverse model after the estimation process by the recursive least square (RLS) method. One solution is to use the all pass filtering (APF) technique t...

      One of the problems of the inverse model-based control techniques is the stability of the identified inverse model after the estimation process by the recursive least square (RLS) method. One solution is to use the all pass filtering (APF) technique to transform non-minimum phase models into minimum phase models [9]. However, there are several cases not cured by the all pass filtering method when the all pass filter algorithm is implemented on the hardware. In this paper, an improved version of the all pass filtering technique is presented to deal with the non-minimum phase models. The factorized APF (fAPF) technique for non-minimum phase models is presented to suggest a simple solution. A simple method for avoiding the calculation of complex numbers is also presented for the easy implementation. Several examples are given to support the proposal.

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      참고문헌 (Reference)

      1 이상덕, "한 바퀴 로봇의 균형제어를 위한 외란관측기의 Q 필터 설계를 통한 실험" 제어·로봇·시스템학회 23 (23): 948-954, 2017

      2 P. A. Regalia, "The digital all-pass filter: a versatile signal processing building block" 76 (76): 19-37, 1988

      3 E. Sariylildiz, "Stability and robustness of disturbance-observer-based motion control systems" 62 (62): 414-422, 2015

      4 L. Ljung, "Perspectives on system identification" 34 (34): 1-12, 2010

      5 Atsushi Fujimori, "Order Reduction of Plant and Controller in Closed Loop Identification based on Joint Input-Output Approach" 제어·로봇·시스템학회 15 (15): 1217-1226, 2017

      6 Y. H. Eng, "Online system identification of an autonomous underwater vehicle via in-field experiments" 41 (41): 5-17, 2016

      7 K. Katsura, "Modeling of force sensing and validation of disturbance observer for force control" 54 (54): 530-538, 2007

      8 박정민, "Extended Least Square Unbiased FIR Filter for Target Tracking Using the Constant Velocity Motion Model" 제어·로봇·시스템학회 15 (15): 947-951, 2017

      9 M. Beza, "A modified RLS algorithm for online estimation of low-frequency oscillations in power systems" 31 (31): 1703-1714, 2016

      1 이상덕, "한 바퀴 로봇의 균형제어를 위한 외란관측기의 Q 필터 설계를 통한 실험" 제어·로봇·시스템학회 23 (23): 948-954, 2017

      2 P. A. Regalia, "The digital all-pass filter: a versatile signal processing building block" 76 (76): 19-37, 1988

      3 E. Sariylildiz, "Stability and robustness of disturbance-observer-based motion control systems" 62 (62): 414-422, 2015

      4 L. Ljung, "Perspectives on system identification" 34 (34): 1-12, 2010

      5 Atsushi Fujimori, "Order Reduction of Plant and Controller in Closed Loop Identification based on Joint Input-Output Approach" 제어·로봇·시스템학회 15 (15): 1217-1226, 2017

      6 Y. H. Eng, "Online system identification of an autonomous underwater vehicle via in-field experiments" 41 (41): 5-17, 2016

      7 K. Katsura, "Modeling of force sensing and validation of disturbance observer for force control" 54 (54): 530-538, 2007

      8 박정민, "Extended Least Square Unbiased FIR Filter for Target Tracking Using the Constant Velocity Motion Model" 제어·로봇·시스템학회 15 (15): 947-951, 2017

      9 M. Beza, "A modified RLS algorithm for online estimation of low-frequency oscillations in power systems" 31 (31): 1703-1714, 2016

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      학술지 이력

      학술지 이력
      연월일 이력구분 이력상세 등재구분
      2023 평가예정 해외DB학술지평가 신청대상 (해외등재 학술지 평가)
      2020-01-01 평가 등재학술지 유지 (해외등재 학술지 평가) KCI등재
      2010-01-01 평가 등재학술지 유지 (등재유지) KCI등재
      2009-12-29 학회명변경 한글명 : 제어ㆍ로봇ㆍ시스템학회 -> 제어·로봇·시스템학회 KCI등재
      2008-01-01 평가 등재학술지 유지 (등재유지) KCI등재
      2007-10-29 학회명변경 한글명 : 제어ㆍ자동화ㆍ시스템공학회 -> 제어ㆍ로봇ㆍ시스템학회
      영문명 : The Institute Of Control, Automation, And Systems Engineers, Korea -> Institute of Control, Robotics and Systems
      KCI등재
      2005-01-01 평가 등재학술지 선정 (등재후보2차) KCI등재
      2004-01-01 평가 등재후보 1차 PASS (등재후보1차) KCI등재후보
      2002-07-01 평가 등재후보학술지 선정 (신규평가) KCI등재후보
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      학술지 인용정보

      학술지 인용정보
      기준연도 WOS-KCI 통합IF(2년) KCIF(2년) KCIF(3년)
      2016 1.35 0.6 1.07
      KCIF(4년) KCIF(5년) 중심성지수(3년) 즉시성지수
      0.88 0.73 0.388 0.04
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