• Title, Summary, Keyword: RLS method

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Low-Complexity VFF-RLS Algorithm Using Normalization Technique (정규화 기법을 이용한 낮은 연산량의 가변 망각 인자 RLS 기법)

  • Lee, Seok-Jin;Lim, Jun-Seok;Sung, Koeng-Mo
    • The Journal of the Acoustical Society of Korea
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    • v.29 no.1
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    • pp.18-23
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    • 2010
  • The RLS (Recursive Least Squares) method is a broadly used adaptive algorithm for signal processing in electronic engineering. The RLS algorithm shows a good performance and a fast adaptation within a stationary environment, but it shows a Poor performance within a non-stationary environment because the method has a fixed forgetting factor. In order to enhance 'tracking' performances, BLS methods with an adaptive forgetting factor had been developed. This method shows a good tracking performance, however, it suffers from heavy computational loads. Therefore, we propose a modified AFF-RLS which has relatively low complexity m this paper.

Time Variant Parameter Estimation using RLS Algorithm with Adaptive Forgetting Factor Based on Newton-Raphson Method (Newton-Raphson법 기반의 적응 망각율을 갖는 RLS 알고리즘에 의한 원격센서시스템의 시변파라메타 추정)

  • Kim, Kyung-Yup;Lee, Joon-Tark
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • pp.435-439
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    • 2007
  • This paper deals with RLS algorithm using Newton-Raphson method based adaptive forgetting factor for a passive telemetry RF sensor system in order to estimate the time variant parameter to be included in RF sensor model. For this estimation with RLS algorithm, phasor typed RF sensor system modelled with inductive coupling principle is used. Instead of applying constant forgetting factor to estimate time variant parameter, the adaptive forgetting factor based on Newton-Raphson method is applied to RLS algorithm without constant forgetting factor to be determined intuitively. Finally, we provide numerical examples to evaluate the feasibility and generality of the proposed method in this paper.

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An Approximated RLS Algorithm for Adaptive Parameter Estimation (적응 파라미터 예측을 위한 근사화된 RLS 알고리즘)

  • Ahn, Bong-Man;Hwang, Jee-Won;Ryoo, Jung-Rae;Cho, Ju-Phil
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.32 no.9C
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    • pp.922-928
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    • 2007
  • This paper presents the fast adaptive algorithm which applies an approximation scheme into RLS algorithm. The proposed algorithm(D-RLS) derives a QRD RLS algorithm derivation process from RLS algorithm recursively. D-RLS has the similar pattern as the algorithm having the approximation that input signals are separated respectively. Computational complexity of D-RLS is O(N), fewer than $O(N^2)$. To evaluate performance of proposed algorithm, we use the system identification method of FIR and Volterra system. And, finally, we can show D-RLS has an excellent performance.

Estimation of Voltage Instability Index Using RLS(Recursive Least Square) (RLS(Recursive Least Square)를 이용한 전압안정도 지수 평가)

  • Jeon, Woong-Jae;Lee, Byong-Jun
    • Proceedings of the KIEE Conference
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    • pp.279-281
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    • 2006
  • A Voltage Instability Predictor(VIP) estimates the proximity of a power system to voltage collapse in real time. Voltage Instability Index(Z-index) from VIP algorithm is estimated using LS(Least Square) method. But this method has oscillations and noise of result due to the system's changing conditions. To suppress oscillations, a larger data window needs to be used. In this paper. I propose the new other method which improves that weakness. It uses RLS(Recursive Least Square) to estimate voltage instability index without a large moving data window so this method is suitable for on-line monitor and control in real time. In order to verify effectiveness of the algorithm using RLS method, the method is tested on HydroQuebec system in real time digital simulator(HYPERSIM).

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Exponentially Weighted Sliding Window RLS Method for Parameter Estimation (파라메타 추정을 위한 지수 함수적 Sliding window RLS 방식)

  • Choi, Bong-Yeol;Lee, Jie-Tae;Bien, Zeung-Nam
    • Proceedings of the KIEE Conference
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    • pp.109-111
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    • 1989
  • In this paper, we propose a new method of parameter est mat ion which modifies the exponentially weighted RLS (WRLS) method using asliding window. It can be used in adaptive control for a class of linear tine varying system. Computer simulations show that our new method tracts rapidly time varying parameters more effectively than WRLS.

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QRD-RLS Algorithm Implementation Using Double Rotation CORDIC (2회전 CORDIC을 이용한 QRD-RLS 알고리듬 구현)

  • 최민호;송상섭
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.29 no.5C
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    • pp.692-699
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    • 2004
  • In this paper we studied an implementation of QR decomposition-based RLS algorithm using modified Givens rotation method. Givens rotation can be obtained with a sequence of the CORDIC operations. In order to reduce the computing time of QR decomposition we restricted the number of iterations of the CORDIC operation per a Givens rotation and used double-rotation method to remove the square-root in the scaling factor.

Experimental Study on a Monte Carlo-based Recursive Least Square Method for System Identification (몬테카를로 기반 재귀최소자승법에 의한 시스템 인식 실험 연구)

  • Lee, Sang-Deok;Jung, Seul
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.67 no.2
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    • pp.248-254
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    • 2018
  • In this paper, a Monte Carlo-based Recursive Least Square(MC-RLS) method is presented to directly identify the inverse model of the dynamical system. Although a RLS method has been used for the identification based on the deterministic data in the closed loop controlled form, it would be better for RLS to identify the model with random data. In addition, the inverse model obtained by inverting the identified forward model may not work properly. Therefore, MC-RLS can be used for the inverse model identification without proceeding a numerical inversion of an identified forward model. The performance of the proposed method is verified through experimental studies on a control moment gyroscope.

Time-Varying Parameter Estimation of Passive Telemetry RF Sensor System Using RLS Algorithm (RLS 알고리즘을 이용한 원격 RF 센서 시스템의 시변 파라메타 추정)

  • Kim, Kyung-Yup;Yu, Dong-Gook;Lee, Joon-Tark
    • Proceedings of the KIEE Conference
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    • pp.29-33
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    • 2007
  • In this paper, time-varying parameter of passive telemetry RF sensor system is estimated using RLS(Rescursive $\leq$* Square) algorithm. In order to overcome the problems such as power limits and complication that general RF sensor system including IC chip has, the principle of inductive coupling is applied to model sensor system The model parameter is rearranged for applying RLS algorithm based on mathematical model to the derived model using inductive coupling principle. Time variant parameter of rearranged model is estimated using forgetting factor, and in case measured data is contaminated by noise and modelling error, the performance of RLS algorithm characterized by the convergence of squared error sum is verified by simulation.

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Capacitive Parameter Estimation of Passive Telemetry RF Sensor System Using RLS Algorithm (RLS 알고리즘을 이용한 원격 RF 센서 시스템의 정전용량 파라메타 추정)

  • Kim, Kyung-Yup;Lee, John-Tark
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.57 no.5
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    • pp.858-865
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    • 2008
  • In this paper, Capacitive Telemetry RF Sensor System using Recursive Least Square (RLS) algorithm was proposed. General Telemetry RF Sensor System means that it should be "wireless", "implantable" and "batterless". Conventional Telemetry RF Sensor System adopts Integrated Circuit type, but there are many defects like complexity of structure and the limitation of large power consumption in some cases. In order to overcome these disadvantages, Telemetry RF Sensor System based on inductive coupling principle was proposed in this paper. Proposed Telemetry RF Sensor System is very simple because it consists of R, L and C and measures the changes of environment like pressure and humidity in the type of capacitive value. This system adopted RLS algorithm for estimation of this capacitive parameter. For the purpose of applying RLS algorithm, proposed system was mathematically modelled with phasor method and was quasi-linearized. As two parameters such as phase and amplitude of output voltage for estimation were needed, Phase Difference Detector and Amplitude Detector were proposed respectively which were implemented using TMS320C2812 made by Texas Instrument. Finally, It is verified that the capacitance of proposed telemetry RF Sensor System using RLS algorithm can be estimated efficiently under noisy environment.

Implementation of Self-Tuning Speed Controller for DC Motor Drive System using RLS Algorithm and Pole-Placement Method (RLS 알고리즘과 극점배치방법을 이용한 DC전동기의 자기동조 속도제어기의 구현)

  • Cha, Eung-Seok;Ji, Jun-Keun
    • Proceedings of the KIEE Conference
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    • pp.488-490
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    • 1999
  • This paper describes the design of self-tuning speed controller for DC motor drive system using RLS(Recursive Least Squares) algorithm and Pole-Placement method. The model parameters, related to inertia and damping coefficient of motor, are estimated on-line by using RLS estimation algorithm. And a control signal is calculated by using pole placement method. Simulation and experimental results show that the proposed controller possesses excellent adaptation capability than a conventional PI/IP controller under parameter change.

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