• 제목/요약/키워드: Recursive least-squares identification

검색결과 27건 처리시간 0.024초

Adaptive System Identification Using an Efficient Recursive Total Least Squares Algorithm

  • Choi, Nakjin;Lim, Jun-Seok;Song, Joon-Il;Sung, Koeng-Mo
    • The Journal of the Acoustical Society of Korea
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    • 제22권3E호
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    • pp.93-100
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    • 2003
  • We present a recursive total least squares (RTLS) algorithm for adaptive system identification. So far, recursive least squares (RLS) has been successfully applied in solving adaptive system identification problem. But, when input data contain additive noise, the results from RLS could be biased. Such biased results can be avoided by using the recursive total least squares (RTLS) algorithm. The RTLS algorithm described in this paper gives better performance than RLS algorithm over a wide range of SNRs and involves approximately the same computational complexity of O(N²).

RLS (Recursive Least Squares)와 RTLS (Recursive Total Least Squares)의 결합을 이용한 새로운 FIR 시스템 인식 방법 (FIR System Identification Method Using Collaboration Between RLS (Recursive Least Squares) and RTLS (Recursive Total Least Squares))

  • 임준석;편용국
    • 한국음향학회지
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    • 제29권6호
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    • pp.374-380
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    • 2010
  • 잡음이 섞인 입출력 신호를 갖는 시스템 인식 문제는 완전 최소 자승법 (Total Least Squares (TLS))으로 알려져 있다. 완전 최소 자승법의 성능은 입력 신호 부가 잡음 파워와 출력 신호 부가 잡음간의 분산비에 매우 민감하다. 본 논문에서는 TLS의 성능 향상을 위해서 LS (Least Squares)와의 결합을 제안한다. 그 한 형태로 재차적인 TLS (Recursive TLS)와 재차적인 LS (Recursive Least Squares)간의 결합 알고리즘을 제안한다. 이 결합은 잡음간 분산비에 강인한 결과를 낳았다. 모의실험을 통해 얻은 결과로부터 입력 신호에 신호대 잡음비가 5dB를 유지히는 잡음을 부가할 경우 입력 잡음과출력 잡음의 비 $\gamma$가 약 20 정도까지로 적용 범위가 확대되는 결과를 얻었다. 따라서 제안된 결합 방법이 기존의 TLS의 적용 범위를 넓힐 수 있음을 알 수 있다.

소형 무인 헬리콥터의 시스템 식별 (System Identification of a Small Unmanned Rotorcraft)

  • 류성숙;송용규
    • 제어로봇시스템학회논문지
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    • 제15권1호
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    • pp.44-53
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    • 2009
  • In this paper, Recursive Least Squares (RLS) and Fourier Transform Regression (FTR) methods for estimating stability and control derivatives of small unmanned helicopter are evaluated together with MMLE technique. Flight data simulated by using a commercial small-scale helicopter model are exploited to estimate the parameters with accuracies for hover and cruise modes. The performances of the system identification methods are also compared by analyzing the responses of the reconstructed systems using estimated derivatives.

QR 분해법을 이용한 적응 쌍선형 격자 알고리듬 (QR-Decomposition based Adaptive Bbilinear Lattice Algorithms)

  • 안봉만;황지원;백흥기
    • 전자공학회논문지B
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    • 제31B권10호
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    • pp.32-43
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    • 1994
  • This paper presents new QRD-based recursive least squares algorithms for bilinear lattice filter. Bilinear recursive least square lattice algorithms are derived by using the QR decomposition for minimization covariance matrix of predication error by applying Givens rotation to the bilinear recursive least squares lattics algorithms. The proposed algorithms are applied to the bilinear system identification to evaluate the performance of algoithms. Computer simulations show that the convergence properties of the proposed algorithms are superior to that of the algorithms proposed by Baik when signal includes the measurement noise.

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실시간 공칭 모델 추정 외란관측기에 관한 실험 연구: 재귀최소자승법 (An Experimental Study on Realtime Estimation of a Nominal Model for a Disturbance Observer: Recursive Least Squares Approach)

  • 이상덕;정슬
    • 제어로봇시스템학회논문지
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    • 제22권8호
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    • pp.650-655
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    • 2016
  • 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.

오차 자기 순환 신경회로망을 이용한 현가시스템 인식과 슬라이딩 모드 제어기 개발 (Identification of suspension systems using error self recurrent neural network and development of sliding mode controller)

  • 송광현;이창구;김성중
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
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    • pp.625-628
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    • 1997
  • In this paper the new neural network and sliding mode suspension controller is proposed. That neural network is error self-recurrent neural network. For fast on-line learning, this paper use recursive least squares method. A new neural networks converges considerably faster than the backpropagation algorithm and has advantages of being less affected by the poor initial weights and learning rate. The controller for suspension systems is designed according to sliding mode technique based on new proposed neural network.

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리튬이온 배터리의 과전압/저전압을 막기 위한 회기 최소 자승법 기반의 실시간 내부 저항 추정방법 (Online Identification of Li-ion Battery's Internal Resistance based on a Recursive Least Squares Method to Prevent Overvoltage/Undervoltage)

  • 김우용;이평연;김종훈;김경수
    • 전력전자학회:학술대회논문집
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    • 전력전자학회 2018년도 전력전자학술대회
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    • pp.237-239
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    • 2018
  • This paper proposes an on-line estimation algorithm of internal resistance of Li-ion battery based on the recursive least squares method to prevent the overvoltage and undervoltage casing degradation of life cycle of battery. An equivalent circuit model with single time constant is adopted, and under assumptions that the terminal voltage, current and SOC are measured accurately, the discrete time based nonlinear equation of the model can be converted to the linear equation which can be applied to recursive least squares method. Since the coefficients of the discrete time linear equation can be expressed by the parameters of the equivalent circuit model, it is shown that an internal resistance (Ri) can be estimated in real time using the least square method.

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미지 부하 질량을 갖는 유연 링크 로봇의 $H_{\infty}$ 자기 동조 제어 ($H_{\infty}$ Self-Tuning Control of a Flexible Link Robot with Unknown Payload)

  • 한기봉;이시복
    • 한국정밀공학회지
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    • 제14권2호
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    • pp.160-168
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    • 1997
  • A $H_{\infty}$self-tuning control scheme for the tip position of a flexible link robot handling unknown loads is presented here. The scheme essentially comprises a recursive least-squares identification algorithm and $H_{\infty}$self-tunning controller. The $H_{\infty}$control low is designed to be robust to uncertain parameters and the self-tunning action provides adaption to unknown parameters. Through numerical study, the performance comparison of the $H_{\infty}$self-tuning controller with a constant gain $H_{\infty}$controller as well as a LQG self-tuning controller clearly shows its superior ability in handling load changes in quiescent states.nt states.

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Development of the structural health record of containment building in nuclear power plant

  • Chu, Shih-Yu;Kang, Chan-Jung
    • Nuclear Engineering and Technology
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    • 제53권6호
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    • pp.2038-2045
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    • 2021
  • The main objective of this work is to propose a reliable routine standard operation procedures (SOP) for structural health monitoring and diagnosis of nuclear power plants (NPPs). At present, NPPs have monitoring systems that can be used to obtain the quantitative health record of containment (CTMT) buildings through system identification technology. However, because the measurement signals are often interfered with by noise, the identification results may introduce erroneous conclusions if the measured data is directly adopted. Therefore, this paper recommends the SOP for signal screening and the required identification procedures to identify the dynamic characteristics of the CTMT of NPPs. In the SOP, three recommend methods are proposed including the Recursive Least Squares (RLS), the Observer Kalman Filter Identification/Eigensystem Realization Algorithm (OKID/ERA), and the Frequency Response Function (FRF). The identification results can be verified by comparing the results of different methods. Finally, a preliminary CTMT healthy record can be established based on the limited number of earthquake records. It can be served as the quantitative reference to expedite the restart procedure. If the fundamental frequency of the CTMT drops significantly after the Operating Basis Earthquake and Safe Shutdown Earthquake (OBE/SSE), it means that the restart actions suggested by the regulatory guide should be taken in place immediately.

초저전력 마이크로 서보시스템의 모델식별을 위한 계측 파라미터 선정 기법 (Sensing Parameter Selection Strategy for Ultra-low-power Micro-servosystem Identification)

  • 한봉수
    • 제어로봇시스템학회논문지
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    • 제20권8호
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    • pp.849-853
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    • 2014
  • In micro-scale electromechanical systems, the power to perform accurate position sensing often greatly exceeds the power needed to generate motion. This paper explores the implications of sampling rate and amplifier noise density selection on the performance of a system identification algorithm using a capacitive sensing circuit. Specific performance objectives are to minimize or limit convergence rate and power consumption to identify the dynamics of a rotary micro-stage. A rearrangement of the conventional recursive least-squares identification algorithm is performed to make operating cost an explicit function of sensor design parameters. It is observed that there is a strong dependence of convergence rate and error on the sampling rate, while energy dependence is driven by error that may be tolerated in the final identified parameters.