• 한국통신학회논문지
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• 제32권11C호
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• pp.1127-1133
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• 2007

제안된 알고리즘은 QR 형태의 LMS 알고리즘이 입력의 분산에 비례하게 되어있어 입력의 분산을 평균적인 측면에서 입력의 분산을 정규화하는 알고리즘중 하나이다. 본 논문에는 정규화 알고리즘의 수렴 특정 분석이 되어있다. 제안한 알고리즘의 성능분석을 위하여 간단한 FIR 시스템의 시스템 식별을 수행하였다. 이때 성능 비교에 참여한 알고리즘은 LMS, NLMS(normalized least mean square) 알고리즘이다. 그 결과 제안한 알고리즘은 NLMS 알고리즘과 매우 유사한 성능을 가짐을 확인하였다.

• 로봇학회논문지
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• 제13권1호
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• pp.55-62
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• 2018

In this paper, a method for estimation of external force on an end-effector using joint torque sensor is proposed. The method is based on portion of measure torque caused by external force. Due to noise in the torque measurement data from the torque sensor, a recursive least-square estimation algorithm is used to ensure a smoother estimation of the external force data. However it is inevitable to create a delay for the sensor to detect the external force. In order to reduce the delay, modified recursive least-square is proposed. The performance of the proposed estimation method is evaluated in an experiment on a developed six-degree-of-freedom robot. By using NI DAQ device and Labview, the robot control, data acquisition and The experimental results output are processed in real time. By using proposed modified RLS, the delay to estimate the external force with the RLS is reduced by 54.9%. As an experimental result, the difference of the actual external force and the estimated external force is 4.11% with an included angle of $5.04^{\circ}$ while in dynamic state. This result shows that this method allows joint torque sensors to be used instead of commonly used external sensory system such as F/T sensors.

• 한국음향학회지
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• 제22권1호
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• pp.1-6
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• 2003

본 논문에서는 시스토릭 어레이 구조를 갖는 선택적 최소분산 비왜곡응답 (MVDR) 및 최소자승 회귀기법 (RLS) 빔형성기법에 대한 성능 분석을 하였다. 원하는 사용자 신호와 잡음을 포함한 스냅샷 벡터들이 어레이 안테나에 입사되는 경우, 수신신호의 품질을 향상시키기 위해서 MVDR 및 RLS 알고리즘을 이용한 빔형성기법이 적용될 수 있다. 이를 통해 채널 용량을 증가시키기 위해 각 안테나 소자의 출력에 복소 가중치를 곱하여 원하는 사용자 신호방향으로 안테나의 빔을 형성하도록 하여 원하는 신호의 다중경로 성분들은 강조하고, 간섭 성분들의 입사 방향들로는 널을 발생시켜 다중간섭과 잡음에 대한 전력을 상대적으로 감소시키는 공간필터링 효과를 얻을 수 있다. 본 논문에서는 이러한 공간 필터 역할을 하는 MVDR기법과 RLS 기법을 병렬처리를 통해 수행할 수 있는 시스토릭 어레이 구조의 MVDR 및 RLS 빔형성기법에 대하여 소개하며, 이를 다중 경로와 다중 접속 간섭이 존재하는 채널 환경에 적용하여 수신 성능을 분석하였다. 컴퓨터 모의 실험을 통하여 제안된 시스토릭 어레이 구조의 빔 형성기법을 적용한 공간필터의 우수성을 보여주기 위해 사용자 증가에 따른 BER (Bit Error Rate) 곡선과 빔패턴을 제시하였고, 기대치와 실험치가 잘 부합됨을 확인하였다.

• 드라이브 ㆍ 컨트롤
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• 제13권4호
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• pp.59-67
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• 2016

This paper proposes a model-prediction-based collision-avoidance algorithm for excavators for which the recursive-least-squares (RLS) estimation of the excavator's rotational inertia is used. To estimate the rotational inertia of the excavator, the RLS estimation with multiple forgetting and two updating rules for the nominal parameter and the forgetting factors was conducted based on the excavator-swing dynamics. The average value of the estimated rotational inertia that is for the minimizing effects of the estimation error was computed using the recursive-average method with forgetting. Based on the swing dynamics, the computed average of the rotational inertia, the damping coefficient for braking, and the excavator's braking angle were predicted, and the predicted braking angle was compared with the detected-object angle for a safety evaluation. The safety level defined in this study consists of the three levels safe, warning, and emergency braking. The analytical rotational-inertia-based performance evaluation of the designed estimation algorithm was conducted using a typical working scenario. The results of the safety evaluation show that the predictive safety-evaluation algorithm of the proposed model can evaluate the safety level of the excavator during its operation.

• 한국지능시스템학회논문지
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• 제15권4호
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• pp.505-510
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• 2005

제어 입력 선택 문제에 있어서 확률적 전략을 활용하는 RPO(randomized policy optimizer) 기법은 최근에 개발된 강화학습 기법으로써, 많은 적용 사례를 통해서 그 가능성이 입증되고 있다 본 논문에서는, 수정된 RPO 알고리즘을 제안하는데, 이 수정된 알고리즘의 크리틱 네트워크 부분은 RLS(recursive least square) 기법을 통하여 갱신된다. 수정된 RPO 기법의 효율성을 확인하기 위해 Kimura에 의해서 연구된 로봇에 적용하여 매우 우수한 성능을 관찰하였다. 또한, 매트랩 애니메이션 프로그램의 개발을 통해서, 로봇의 이동이 시간에 따라 가속되는 학습 알고리즘의 효과를 시각적으로 확인 할 수 있었다.

• 전력전자학회:학술대회논문집
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• 전력전자학회 2000년도 전력전자학술대회 논문집
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• pp.232-236
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• 2000

In this paper a novel estimation algorithm of mechanical parameters in two-mass system is proposed. The inertia of a load and a motor and the stiffness are estimated by using RLS (Recursive Least Square) algorithm and acceleration information of motor. The effectiveness of the proposed scheme is verified with simulation and experiments results.

• 대한전기학회논문지:시스템및제어부문D
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• 제51권4호
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• pp.129-136
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• 2002

This paper presents a $H_{\infty}$ robust controller with parameter estimation in polynomial approach. For good performance of a uncertain system, the parameters are estimated by RLS algorithm. The controller minimizes the sum of $H_{\infty}$ norm between sensitivity function and complementary sensitivity function by employing the Youla parameterization and polynomial approach at the same time. A numerical example and its simulation results are given to show the validity of the proposed controller.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1997년도 춘계학술대회 논문집
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• pp.766-771
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• 1997

In this strip casting,size of the roll separating force is a index representing the solidifying status of the melt. Rolling forces at the start of the casting process can change abruptly due to the overcooling of the leader strip. This inconsistensy leads to machine damage or deficient solidification which results in the failure of the casting. In this study, a mathematical model is derived for the hydraulic servo pressure control system for the twin roll strip caster and its parameters are estimated by the RLS algorithm. Based on the identified model, an one-step ahead predictive control method is applied in order to minimize the transient fluctuation of the rolling force. Its simulation results are compared with those of the conventional PI controllers.

• 전기학회논문지
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• 제56권2호
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• pp.311-316
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• 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.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2007년도 심포지엄 논문집 정보 및 제어부문
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• pp.86-88
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• 2007

In the semiconductor manufacturing industry, the heterodyne laser interferometer plays as an ultra-precise measurement system. However, the heterodyne laser interferometer has some unwanted nonlinearity error which is caused from frequency-mixing. This is an obstacle to improve the measurement accuracy in nanometer scale. In this paper we propose a compensation algorithm based on RLS(recursive least square) method and artificial intelligence method, which reduce the nonlinearity error in the heterodyne laser interferometer. With the capacitance displacement sensor we get a reference signal which can be transformed into the intensity domain. Using the back-propagation Neural Network method, we train the network to track the reference signal. Through some experiments, we demonstrate the effectiveness of the proposed algorithm in measurement accuracy.