• 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.

• Journal of the Korean Society for Precision Engineering
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• v.12 no.11
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• pp.110-117
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• 1995

This study presents and algorithm and related techniques which could satisfy the important properties of check weighers and conveyor scales. The algorithm of Recursive Least Squares Regression is applied for the weighing system simulated as a dynamic model of the second order. Using the model and the algorithm, model parameters and then the mass being weighed can be determined from the step input. The performance of the algorithm was tested on a check weigher. Discussions were extended to the development of noise reduction techniques and to the lagged introduction of objects on the moving plate. It turns out that the algorithm shows several desirable features suitable for real-time signal processing with a microcomputer, which are high precision and stability in noisy environment.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.8
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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.

• Proceedings of the KIEE Conference
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• 2003.07d
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• pp.2017-2019
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• 2003

열악한 환경에서 동작해야 하거나 물리적 접근이 어려운 곳에 장착되는 센서 시스템의 경우, 유선에 의한 정보전달이 어려울 뿐만 아니라 센서 내 전원설비가 제한적인 수도 있다. 따라서 본 논문에서는 이러한 문제점에 대한 해결책으로서 밧데리없이 유도결합에 의하여 원격 센서로부터 정보 취득이 가능한 한 방법을 제안하였다. 이 방법은 전원공급에 의한 유도 결합식의 원격 센서 시스템과는 달리, 원격 센서의 정전용량을 변 복조 과정 없이 재귀적 최소 자승 추정법에 의해 센서의 정전용량을 고정도로 추정하는 것이다. 이를 위하여 시 스템의 유도결합 모델을 사용하였으며, 모델 파라미터가 시간에 따라 변화하는 경우에는 망각률을 사용하여 정확도가 높은 원격 센서 시스템을 구현할 수 있었다.

• Journal of the Korean Society for Precision Engineering
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• v.11 no.6
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• pp.136-142
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• 1994

This study presents an algorithm and related techniques which could satisfy the important properties of check weighers and conveyor scales. The algorithm of Recursive Least Squares Regression is described for te weighing system simulated as a dynamic model of the second order. Using the model and the algorithm, model parameters and then the mass being weighed can be determined from the step input. The performance of the algorithm is illustrated in digital simulation. Discussions are extended to the development of fast converging algorithm. It turns out that the algorithm shows several desirable features suitable for microcomputer assisted real-time signal processing, which are high precision and stability in noisy environment.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.12
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• pp.2246-2253
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• 2011

This paper presents the error correction method of magnetic position sensor using recursive least square method (RLSM) with forgetting factor. Magnetic position sensor is proposed for linear position detection of the linear motor which has tooth shape stator, consists of permanent magnet, iron core and linear hall sensor, and generates sine and cosine waveforms according to the movement of the mover of the linear motor. From the output of magnetic position sensor, the position of the linear motor can be detected using arc-tan function. But the variation of the air gap between magnetic position sensor and the stator and the error in manufacturing process can cause the variation in offset, phase and amplitude of the generated waveforms when the linear motor moves. These variations in sine and cosine waveforms are changed according to the current linear motor position, and it is very difficult to compensate the errors using constant value. In this paper, the generated sine and cosine waveforms from the magnetic position sensor are compensated on-line using the RLSM with forgetting factor. And the speed observer is introduced to reduce the effect of uncompensated harmonic component. The approaches are verified by some simulations and experiments.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.3
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• pp.427-432
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• 2018

This paper uses a recursive least squares method to estimate the projectile motion trajectory of an object in real time. The equations of motion of the object are obtained considering the air resistance which occurs in the actual experiment environment. Because these equations consider air resistance, parameter estimation of nonlinear terms is required. However, nonlinear recursive least squares estimation is not suitable for estimating trajectory of projectile in that it requires a lot of computation time. Therefore, parameter estimation for real-time trajectory prediction is performed by recursive least square estimation after using Taylor series expansion to approximate nonlinear terms to polynomials. The proposed method is verified through experiments by using VICON Bonita motion capture system which can get three dimensional coordinates of projectile. The results indicate that proposed method is more accurate than linear Kalman filter method based on the equations of motion of projectile that does not consider air resistance.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.802-803
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• 2011

매입형 영구자석 동기전동기는 강건한 회전자 구조와 릴럭턴스 토크를 사용할 수 있다는 점, 악계자 제어를 하기 쉽다는 점에서 넓은 속도와 토크를 필요로하는 하이브리드 차량이나 전기 차량에 적합한 전동기이다. 영구자석의 감자곡선은 온도에도 의존하기 때문에 온도에 따라 전동기의 자속과 토크가 변하게 된다. 이 논문은 전기 스쿠터에 사용되는 매입형 영구자석 동기전동기의 온도에 따른 지령 전류 보정에 의한 제어법에 대해 연구하였다. 토크 리플을 줄이기 위해서 속도-토크 곡선과 감자곡선을 이용하여 구하였으며, 보정된 지령 전류를 구하기 위해 Lagrange 보간법과 재귀 최소자승(Recursive Least Square : RLS) 법을사용하여 전류맵을 만들었다.이 지령 전류는 토크와 인버터 출력 전류값을 계산하는데 사용된다. 전류맵을 만들기 위해서 측정한 온도는 20, 80, 100도이다. 본 논문에서 제안한 제어법을 이용하여 토크 리플이 줄어듬을 시뮬레이션과 실험을 통해서 확인할 수 있었다.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.2
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• pp.204-210
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• 2005

This paper presents online identification algorithm for TSK fuzzy model. The proposed algorithm identify structure of premise part by using distance, and obtain the parameters of the piecewise linear function consisting consequent part by using recursive least square. Only input space was considered in Most researches on structure identification, but input and output space is considered in the proposed algorithm. By doing so, outliers are excluded in clustering effectively. The existing other algorithm has disadvantage that it is sensitive to noise by using data itself as cluster centers. The proposed algorithm is non-sensitive to noise not by using data itself as cluster centers. Model can be obtained through one pass and it is not needed to memorize many data in the proposed algorithm.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.3
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• pp.224-229
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• 2012

In this paper, we propose a correction method for astronomical telescope using recursive least square method. There are two ways to move a telescope : equatorial operation and altazimuth operation. We must align polar axis of a equatorial telescope with the north celestial pole and adjust the horizontal axis of a altazimuth telescope exactly to match the celestial coordinate system with the telescope coordinate system. This process needs time and expertise. We can skip existing process and correct a tracking error easily by deriving the relationship of the celestial coordinate system and the telescope coordinate system using the proposed correction method. We obtain the coordinate of a celestial body in the celestial coordinate system and the telescope coordinate system and derive a transformation matrix through the obtained coordinate. We use recursive least square method to estimate the unknown parameters of a transformation matrix. Finally, we implement a telescope control system using a microprocessor and verify the performance of the correction method. Through an experiment, we show the validity of the proposed correction method.