• 대한전기학회:학술대회논문집
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• 대한전기학회 1999년도 하계학술대회 논문집 B
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• pp.868-870
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• 1999

In this paper we obtain a discrete mathmatical model of a Boiler control system from expermental data, we find appropriate input signal and parameter estimation algorithm for identification of the Boiler control system in power plant. Under these conditions experimental data are collected from real system and parameters are estimated by the Recursive Least Square algorithm. The computer simulation results show the parameter estimation algorithm for identification and the effectiveness of controller design of the Boiler control system.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1988년도 한국자동제어학술회의논문집(국내학술편); 한국전력공사연수원, 서울; 21-22 Oct. 1988
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• pp.476-481
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• 1988

In this paper a pH process of a weak acid with a strong base is modeled into a bilinear form, and a self-tuning pH control algorithm which is robust against initial values of solution and disturbances is presented. The control algorithm employs the recursive least square method for the parameter estimation and the generalised minimum variance criterion as the objective function. The computer simulation shows that the tracking of desired pH values is obtained in satisfactory manner regardless of the initial values chosen for the process.

• Journal of Advanced Marine Engineering and Technology
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• 제28권4호
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• pp.569-576
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• 2004

In this paper, passive telemetry capacitive humidity sensor system using a RLSE(Recursive Least Square Estimation) technique is proposed. To overcome the problem like power limits and complications that general passive telemetry sensor system including IC chip has, the principle of inductive coupling is applied to model the sensor system. Specially. by applying the forgetting factor we show that the accuracy of its estimation can be improved even in the case of time varying parameter and also the convergence time can be reduced.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2002년도 합동 추계학술대회 논문집 정보 및 제어부문
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• pp.546-549
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• 2002

In this paper, a simulation system, which is almost same with the real motor-mechanical control system, is established. The real system is identified by using the data from DSP(TMS320F240). The RLS(Recursive Least Square) algorithm is used for the identification and MATLAB Simulink program is used for simulation. The exact simulation system obtained by using the proposed method is very useful for analysis and design of motor-mechanical control systems.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1994년도 추계학술대회 논문집
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• pp.371-376
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• 1994

This paper presents an on-line modeling method approach for the machine condition. the machine condition is continuously monitored with a sensor such as, a vibration, a current, an acoustic emission (AE) sensor. In this study, neural network modeling by radial basis function is designed for analysis a prediction error. An on-line learning algorithm is designed using the RLS(recursive least square) estimation and the existing clustering method of Kohonen neural network. Experimental results show that the proposed RBNN modeling is suitable for predicting simulated data.

• 한국식품영양학회지
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• 제1권2호
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• pp.31-36
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• 1988

An adaptive on-line optimization method has been applied to test the ability to maximize the cellular productivity of a continuous methylotroph culture system which was simulated by a variable yield Monod-type model. Optimum dilution rate and productivity were successively obtained and maintained at all times by the algorithm that utilizes steepest descent technique as optimization method and recursive least-square method with forgetting factor as dynamic model identification.

• 전력전자학회:학술대회논문집
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• 전력전자학회 2004년도 추계학술대회 논문집
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• pp.18-20
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• 2004

In this paper, a new technique of inertia identification using recursive least square algorithm and full order estimator is proposed. The speed response is sensitive to variation in machine parameters especially the moment of inertia. The effectiveness of the method has been verified by simulations.

• The Journal of the Acoustical Society of Korea
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• 제12권1E호
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• pp.56-64
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• 1993

본 논문은 공간적으로 변하는 스펙트럼을 추정하는 새로운 적응 방법을 제안한다. 제안한 방법에서는 오래된 upstream의 데이터를 망각함으로서 신호의 nonstationarity를 고려해주는 시변망각인자의 개념을 recursive least square(RLS) 알고리즘에 도입하였으며, 관심이 있는 공간영역에서 탐사침을 천천히 움직여 얻은 하나의 데이터 군으로부터 downstream 스펙트럼을 추정하였다. 제시한 방법의 실현 가능성은 실제 실험(wind tunnel 이용)을 통해서 얻은 공간적으로 변하는 nonstatonary 신호의 스펙트럼을 추정하는 과정에서 입증되며 또한 기존의 방법들과 비교함으로서 그 우수성을 보인다.

• 한국통신학회논문지
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• 제25권5B호
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• pp.830-841
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• 2000

We extend the sue of the method of least square to develop a recursive algorithm for the design of adaptive transversal filters such that, given the least-square estimate of this vector of the filter at iteration n-1, we may compute the updated estimate of this vector at iteration a upon the arrival of new data. We begin the development of the RLS algorithm by reviewing some basic relations that pertain to the method of least squares. Then, by exploiting a relation in matrix algebra known as the matrix inversion lemma, we develop the RLS algorithm. An important feature of the RLS algorithm is that it utilizes information contained in the input data, extending back to the instant of time when the algorithm is initiated. In this paper, we propose new tap weight updated RLS algorithm in adaptive transversal filter with data-recycling buffer structure. We prove that convergence speed of learning curve of RLS algorithm with data-recycling buffer is faster than it of exiting RL algorithm to mean square error versus iteration number. Also the resulting rate of convergence is typically an order of magnitude faster than the simple LMS algorithm. We show that the number of desired sample is portion to increase to converge the specified value from the three dimension simulation result of mean square error according to the degree of channel amplitude distortion and data-recycle buffer number. This improvement of convergence character in performance, is achieved at the (B+1)times of convergence speed of mean square error increase in data recycle buffer number with new proposed RLS algorithm.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2007년도 춘계학술대회 논문집 전기기기 및 에너지변환시스템부문
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• pp.29-33
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• 2007

본 연구에서는 RLS(Rescursive Least Square) 알고리즘을 이용하여 정전용량형 습도센서를 사용한 원격 RF 센서 시스템의 시변 파라메타를 추정하고자 한다. IC 칩 형태의 원격 RF 센서 시스템이 가지는 구성의 복잡성 그리고 전력소모 문제를 해결하기 위해 보다 간단한 유도결합모델이 제안된다. 모델기반의 RLS 알고리즘을 수학적인 모델로 유도된 시스템에 적용시키기 위해 페이저법을 이용하여 모델의 파라메타를 재배열한다. 오차 제곱합의 수렴특성을 가진 RLS 알고리즘을 이용하여 시변 파라메타를 추정하며, 잡음을 내포한 측정 데이터에 대한 추정 성능을 확인함으로써 그 유효성을 검증하고자 한다.