• 한국통신학회논문지
• /
• 제22권7호
• /
• pp.1468-1476
• /
• 1997

상태축약심볼열추정(RSSE: Reduced State Sequence Estimation) 수신기는 비터비 복호기와 채널 추정기로 구성된다. 이동통신과 같이 채널이 변하는 환경에서는 적응 채널추정기(adaptive channel estimator)로 채널의 변화를 계속적으로 추정해야 한다. 일반적으로 사용되는 채널 추정기는 임시결정된 비터비 복호기의 출력을 사용하여 채널을 추정 하는데, 비터비 복호기에서 잘못된 결정을 내릴 경우 이로 인해 오류전파(error propagation)가 발생할 수있다. 본 논문에서는 좀더 정확한 채널 추정과 오류전파를 막기 위해 경로 메모리를 사용하는 새로운 채널추정기를 사용한다. 이 채널 추정기는 비터비 복호기의 여러 경로중에서 가장 작은 경로를 선택하여 그 경로상의 신호를 이용하여 채널 추정을 행한다. 그리고 채널 추정기의 적응 알고리듬으로서 LMS(Least Mean Square)알고리듬과 Recursive Least Square(RLS) 알고리듬을 사용하여 비교한다. 실험 결과를 통해 제안된 채널 추정기를 사용하는 RSSE 수신기가 기존의 채널 추정기를 사용하는 RSSE 수신기에 비해 더 나은 성능을 나타내는 것을 볼 수있으며, 페이딩이 존재하는 이동통신 환경에서는 LMS 알고리듬이 적합하지 않음을 알 수있다.

• 전자공학회논문지B
• /
• 제31B권7호
• /
• pp.33-41
• /
• 1994

A single channel adaptive noise canceling (ANC) technique with a recursive time delay estimator (RTDE) is presented for removing effects of additive noise on the speech signal. While the conventional method makes a reference signal for the adaptive filter using the pitch estimated on a frame basis from the input speech, the proposed method makes the reference signal using the delay estimated recursively on a sample-by-sample basis. As the RTDEs, the recursion formulae of autocorrelation function (ACF) and average magnitude difference function (AMDF) are derived. The normalized least mean square (NLMS) and recursive least square (RLS) algorithms are applied for adaptation of filter coefficients. Experimental results with noisy speech demonstrate that the proposed method improves the perceived speech quality as well as the signal-to-noise ratio and cepstral distance when compared with the conventional method.

• Structural Engineering and Mechanics
• /
• 제34권1호
• /
• pp.1-14
• /
• 2010

The innovative intelligent fuzzy weighted input estimation method which efficiently and robustly estimates the unknown time-varying input force in on-line is presented in this paper. The algorithm includes the Kalman Filter (KF) and the recursive least square estimator (RLSE), which is weighted by the fuzzy weighting factor proposed based on the fuzzy logic inference system. To directly synthesize the Kalman filter with the estimator, this work presents an efficient robust forgetting zone, which is capable of providing a reasonable compromise between the tracking capability and the flexibility against noises. The capability of this inverse method are demonstrated in the input force estimation cases of the plate structure system. The proposed algorithm is further compared by alternating between the constant and adaptive weighting factors. The results show that this method has the properties of faster convergence in the initial response, better target tracking capability, and more effective noise and measurement bias reduction.

• 대한전기학회논문지:전기기기및에너지변환시스템부문B
• /
• 제48권3호
• /
• pp.139-143
• /
• 1999

This paper is on realization of the speed-sensorless vector control of an induction motor using the RLS(Recursive Least Square) algorithm. The speed estimator is including the RLS algorithm and a rotor flux observer. The RLS algorithm has speed and rotor time constant as parameter vectors and rotor flux observer is designed to have robustness to stator resistance variation and through the IP(Integral and Proportional) speed controller stable performance is obtained for estimating rotor speed. Finally the total algorithm are realized in induction motor drive system and its effectiveness is verified.

• Structural Engineering and Mechanics
• /
• 제37권4호
• /
• pp.351-365
• /
• 2011

This study proposes an inverse estimation method for the input forces of a fixed beam structural system. The estimator includes the fuzzy Kalman Filter (FKF) technology and the fuzzy weighted recursive least square method (FWRLSM). In the estimation method, the effective estimator are accelerated and weighted by the fuzzy accelerating and weighting factors proposed based on the fuzzy logic inference system. By directly synthesizing the robust filter technology with the estimator, this study presents an efficient robust forgetting zone, which is capable of providing a reasonable trade-off between the tracking capability and the flexibility against noises. The period input of the fixed beam structure system can be effectively estimated by using this method to promote the reliability of the dynamic performance analysis. The simulation results are compared by alternating between the constant and adaptive and fuzzy weighting factors. The results demonstrate that the application of the presented method to the fixed beam structure system is successful.

• 자동차안전학회지
• /
• 제12권2호
• /
• pp.14-20
• /
• 2020

This paper presents a vehicle mass and road grade estimator for developing an automated bus. To consider the dynamic characteristics of a bus varying with the number of passengers, the longitudinal controller needs the estimation of the vehicle's mass and road grade in real-time and utilizes the information to adjust the control gains. Discrete Kalman filter is applied to estimate the time-varying road grade, and the recursive least squares algorithm is adopted to account for the constant mass estimation. After being implemented in MATLAB/Simulink, the estimators are evaluated with the dynamic model and experimental data of the target bus. The proposed estimators will be applied to complement the algorithm of the longitudinal controller and proceed with algorithm verification.

• 한국음향학회지
• /
• 제14권3호
• /
• pp.37-48
• /
• 1995

일반화된 완전최소자승법 (generalized total least squares method, GTLS)의 ARMA 시스템 식별에의 적용과 GTLS의 적응알고리듬에 대하여 논한다. 일반화된 완전최소자승법은 일별과 출력을 알고 있는 시스템식별 (system identification)문제에서, 출력이 잡음에 의하여 오염된 경우, 편이되지 않은 해를 구하기 위하여 사용되는 방법이다. 본 논문에서는 먼저 GTLS를 ARMA 시스템 식별에 적용하기 위한 formulation을 하고, 일반화된 완전최소자승법의 일반 해의 성질과 역행렬 정리 (matrix inverse lemma)를 이용하여 적응 GTLS 방법을 제안한다. 다음 제안된 방법을 통하여 시스템식별에 적용하여 그 성능을 평가한다. 또한 GTLS 알고리듬과 제안한 적응 GTLS 알고리듬의 성능을 수학적으로 해석하고 컴퓨터 시뮬레이션을 통하여 이를 검증한다.

• 한국통신학회논문지
• /
• 제37C권10호
• /
• pp.1004-1010
• /
• 2012

논문에서는 최근에 무선 센서 관련 연구에서 제안된 높은 정확도를 가진 센서 간의 클락 동기 기술을 멀티스태틱 레이더 시스템을 위한 무선 시간동기 알고리즘에 적용을 고려하고 특히 비가시선 상에 있는 노드들 간에 적용 될 수 없는 기존 이론의 한계를 극복하는 알고리즘을 제안한다. 제안된 알고리즘에서는 두 노드에서의 얻어진 타임 스탬프 관찰 결과 정보를 바탕으로 recursive robust least M-estimation (RLM) 기법을 이용하여 두 개의 센서 노드 간의 상대적인 클락 스큐(skew)와 위상 차이를 추정한다. 그 과정에서 NLOS 환경으로 인해 uplink와 downlink시에 발생하는 지연시간의 차이를 추적하여 억제시킴으로써 알고리즘의 성능 향상시킨다. 또한 mean square error (MSE)를 계산하여 알고리즘의 성능을 기존 maximum-liklihood (ML) 기법을 이용한 알고리즘과 비교 분석한다.

• Wind and Structures
• /
• 제11권1호
• /
• pp.19-33
• /
• 2008

This research investigates the adaptive input estimation method applied to the multilayer shearing stress structure. This method is to estimate the values of wind load inputs by analyzing the active reaction of the system. The Kalman filter without the input term and the adaptive weighted recursive least square estimator are two main portions of this method. The innovation vector can be produced by the Kalman filter, and be applied to the adaptive weighted recursive least square estimator to estimate the wind load input over time. This combined method can effectively estimate the wind loads to the structure system to enhance the reliability of the system active performance analysis. The forms of the simulated inputs (loads) in this paper include the periodic sinusoidal wave, the decaying exponent, the random combination of the sinusoidal wave and the decaying exponent, etc. The active reaction computed plus the simulation error is regard as the simulated measurement and is applied to the input estimation algorithm to implement the numerical simulation of the inverse input estimation process. The availability and the precision of the input estimation method proposed in this research can be verified by comparing the actual value and the one obtained by numerical simulation.

• 전기학회논문지
• /
• 제56권2호
• /
• pp.311-316
• /
• 2007

This paper proposes the algorithm which estimates moment of the inertia and friction coefficient of friction for high performance speed control of electric motor. The proposed algorithm finds the moment of inertia and friction coefficient of friction by observing the speed error signal generated by the speed observer and using Recursive Least-Mean-Square method(RLS). By feedbacking the estimated inertia and estimated coefficient of friction to speed controller and full order speed observer, then the errors of the inertia and coefficient of friction and speed due to the inaccurate initial value are decreased. Inertia and coefficient of friction converge to the actual value within several times of speed changing. Simulation and actual experiment results are given to demonstrate the effectiveness of the proposed parameter estimator.