• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2006년도 춘계학술대회 논문집
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• pp.53-54
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• 2006

The main purpose of tunnel ventilation system is to maintain CO pollutant and VI (visibility index) under an adequate level to provide drivers with safe driving condition. Moreover, it is necessary to minimize power consumption used to operate ventilation system. To achieve the objectives, the control algorithm used in this research is reinforcement teaming (RL) method. RL is a goal-directed teaming of a mapping from situations to actions. The goal of RL is to maximize a reward which is an evaluative feedback from the environment. Constructing the reward of the tunnel ventilation system, two objectives listed above are included. RL algorithm based on actor-critic architecture and natural gradient method is adopted to the system. Also, the recursive least-squares (RLS) is employed to the learning process to improve the efficiency of the use of data. The simulation results performed with real data collected from existing tunnel are provided in this paper. It is confirmed that with the suggested controller, the pollutant level inside the tunnel was well maintained under allowable limit and the performance of energy consumption was improved compared to conventional control scheme.

• 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.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2000년도 ITC-CSCC -1
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• pp.406-409
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• 2000

This paper proposes a method that enables us to implement the recursive least squares (RLS) algorithm at, high throughput rate using fewer processing elements (PEs). It is known that the pipeline processing can provide a high throughput rate. But, pipelining is effective only when enough number of PEs are available. The proposed method achieves high throughput rate using a few PEs. The effectiveness of the proposed method is verified through simulations on programmable digital signal processors (in the following, DSP processors).

• 전기전자학회논문지
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• 제23권3호
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• pp.817-825
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• 2019

마이크로프로세서를 이용한 제어알고리즘 구현에서 차분방정식이 매우 유용하게 사용된다. 샘플링 데이터로부터 미분 값을 추정하기 위해 전향, 후향 및 중심 차분 방식이 사용되어왔다. 차분 값을 계산하기 위해서는 차분계수가 매우 중요하다. 본 논문에서는 유한 차분 계수를 계산하기 위한 새로운 방식을 제시하고자 한다. 제안된 방식의 유효성을 입증하기 위해 RLS 알고리즘을 적용한 파라미터 추정에 대하여 적용하였다.

• Journal of information and communication convergence engineering
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• 제6권3호
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• pp.310-314
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• 2008

This paper proposes a very novel method which makes it possible that state feedback controller can be designed for unknown dynamic system with measurable states. This novel method uses the support vector machines (SVM) with its function approximation property. It works together with RLS (Recursive least-squares) algorithm. The RLS algorithm is used for the identification of input-output relationship. A virtual state space representation is derived from the relationship and the SVM makes the relationship between actual states and virtual states. A state feedback controller can be designed based on the virtual system and the SVM makes the controller with actual states. The results of this paper can give many opportunities that the state feedback control can be applied for unknown dynamic systems.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1995년도 Proceedings of the Korea Automation Control Conference, 10th (KACC); Seoul, Korea; 23-25 Oct. 1995
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• pp.51-55
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• 1995

An adaptive unified predictive control (UPC) algorithm is applied to a batch polymerization reactor for poly(methyl methancrylate) (PMMA) and the effects of controller parameters are investigated. Computational studies are performed for a batch polymerization system model developed in this study. A transfer function in parametric form is estimated by recursive least squares (RLS) method, and the UPC algorithm is implemented to control the reactor temperature on the basis of this transfer function. The adaptive unified predictive controller shows a better performance than the PID controller for tracking set point changes, especially in the latter part of reaction course when gel effect becomes significant. Various performance can be acquired by selecting adequate values for parameters of the adaptive unified predictive controller; in other words, the optimal set of parameters exists for a given set of reaction conditions and control objective.

• 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.

• 전력전자학회:학술대회논문집
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• 전력전자학회 2017년도 전력전자학술대회
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• pp.126-127
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• 2017

An accurate State Of Charge (SOC) estimation of battery is the most important technique for Electric Vehicles (EVs) and Energy Storage Systems (ESSs). In this paper a new integrated Unscented Kalman Filter-Particle Filter (UKF-PF) is employed to estimate the SOC of a $LiFePO_4$ battery cell and a significant improvement is obtained as compared to the other methods. The parameters of the battery is modeled by the second order Auto Regressive eXogenous (ARX) model and estimated by using Recursive Least Square (RLS) method to calculate value of each element in the model. The proposed algorithm is established by combining a parameter identification technique using RLS method with ARX model and an SOC estimation technique using UKF-PF.

• 한국전자파학회논문지
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• 제22권3호
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• pp.312-319
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• 2011

본 논문에서는 디지털 전치 왜곡 선형화기를 위한 새로운 선형화 알고리즘을 제안하였다. 제안된 알고리즘은 DFP(Davidon-Fletcher-Powell) method를 활용하였다. 또한, 기존의 알고리즘보다 빠른 수렴 속도를 가지며, 가중치 갱신 step-size를 초기 설정값 없이 매 루틴마다 최적의 값을 갱신한다. 전력증폭기 모델링에는 전력 증폭기의 기억 효과를 모델링할 수 있는 memory polynomial 모델을 사용하였고, 선형화기의 전체적인 구성은 간접 학습 구조를 따랐다. 제안된 알고리즘의 성능 검증을 위해 기존의 LMS(Least Mean-Squares), RLS(Recursive Least squares) 알고리즘과 비교하였다.

• 수면정신생리
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• 제20권1호
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• pp.15-21
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• 2013

목 적: 하지불안증후군에서의 인지기능 저하는 흔히 동반되는 수면박탈, 불안, 우울 등에 의해 영향을 받는다. 본 연구의 목적은 투약 받지 않고 있는 한국 노인 인구에서 하지불안증후군과 인지기능 저하와의 관련성을 동반 증상의 영향을 배제하고 살펴보는 것이다. 방 법: 연구대상은 25명의 투약 받고 있지 않은 한국 노인 하지불안증후군 환자군과 나이, 성별, 교육연한에 따라 짝지은 50명의 대조군이다. 모든 연구대상에 대해 CERAD-K 신경심리평가, 중증인지감퇴평가 척도, 전두엽 기능 평가, 그리고 시계 그리기 검사(CLOX)를 포함한 광범위한 인지기능 평가를 시행하였다. 또한 수면의 질 평가를 위해 피츠버그 수면의 질 지수(Pittsburgh Sleep Quality Index, PSQI), 우울증의 평가를 위해 노인우울척도(Geriatric Depression Scale, GDS)를 사용하였다. 결 과: 환자군과 대조군 사이의 PSQI와 GDS 점수의 차이는 없었다. 구성 재인 검사에서 환자군이 대조군에 비해 더 낮은 점수를 보였으며(t=-2.384, p=0.02), 이를 제외한 모든 영역의 인지기능 평가에서 환자군과 대조군의 유의미한 차이는 관찰되지 않았다. 우울감이 있는 대상($GDS{\geq}10$)은 그렇지 않은 군에 비해 언어 유창성, 간이 정신상태 검사, 단어목록기억, 길 만들기 검사, 전두엽 기능 평가의 영역에서 유의한 인지기능 저하를 보였다. 수면의 질이 낮은 대상(PSQI>5)은 그렇지 않은 군에 비해 인지기능 평가의 전 영역에서 차이를 보이지 않았다. 결 론: 본 연구에서 하지불안증후군 환자군을 대조군과 비교한 결과 환자군은 불면과 우울의 영향을 배제하면 비교적 인지기능이 보존된 것으로 관찰되었다. 환자군에서 관찰되었던 시각 인지 영역의 저하는 하지불안증후군에서의 도파민 신경전달계의 장애와 연관하여 해석해 볼 수 있다.