• 대한전기학회:학술대회논문집
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• 대한전기학회 2000년도 하계학술대회 논문집 A
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• pp.80-84
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• 2000

Network parameters in power systems are indispensable for all of power system engineering studies, including the power flow calculation and the state estimation. The network parameters required for the studios, in general, are estimated by using several estimation techniques, since it Is very difficult to measure. To improve the estimation accuracy of the network parameters, this paper adopt the synchronized phasor measurements which are acquired from the Phasor Measurement Unit with built-in GPS receiver. In this paper, the parameter estimation problem is formulated with over-determined nonlinear measurement equations and solved with Newton-Raphson method and pseudo-inverse. The effectiveness of the proposed parameter estimation with the synchronized phasor measurements is verified through some case studies with IEEE sample system. The results are very promising.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1993년도 한국자동제어학술회의논문집(국내학술편); Seoul National University, Seoul; 20-22 Oct. 1993
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• pp.314-317
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• 1993

In this paper, the IPE(Iterative Parameter Estimation) methods for the nonlinear measurements are proposed. The IPE methods convert the problems of the parameter estimation for the nonlinear measurements to that of the solution of the nonlinear equations approximately and use several iterative numerical solutions, such as fixed points theory, Newton's methods, quasi-Newton's methods and steepest descent techniques. the IPE methods for the nonlinear measurements-in the case of the error estimation for the inertial navigation systems are simulated, and it is found that the estimation errors for the nonlinear measurements decrease rapidly and converge to almost that of the linear LSE(Least Squares Estimation) when the IPE methods are applied.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.375-375
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• 2000

Estimating software development effort remains a complex problem attracting considerable research attention. Improving the estimation techniques available to project managers would facilitate more effective control of time and budgets in software development as well as market. However, estimation is difficult because of its similarity to export judgment approaches and fur its potential as an expert assistant in support of human judgment. Especially, in software development for DCS (Distributed Control System), because of infrastructure software related to target-machines hardware and process characteristics should be considered, estimating software development effort is more complex. This paper suggests software development effort estimation technique using neural network. The methods considered are based on COCOMO and case-based projects. Estimation results applied to case-based project appeared to have value fur software development effort estimation models.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권11호
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• pp.5365-5380
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• 2016

Estimation of signal-to-noise ratio (SNR) is an important problem in wireless communication systems. It has been studied for various constellation types and channels using different estimation techniques. Maximum likelihood estimation is a technique which provides efficient and in most cases unbiased estimators. In this paper, we have applied maximum likelihood estimation for systems employing square or cross QAM signals which are undergoing slow flat Rayleigh fading. The problem has been considered under various scenarios like data-aided (DA), non-data-aided (NDA) and partially data-aided (PDA) and the performance of each type of estimator has been evaluated and compared. It has been observed that the performance of DA estimator is best due to usage of pilot symbols, with the drawback of greater bandwidth consumption. However, this can be catered for by using partially data-aided estimators whose performance is better than NDA systems with some extra bandwidth requirement.

• 제어로봇시스템학회논문지
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• 제22권10호
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• pp.788-796
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• 2016

Bearing and frequency measurements of TMA (Target Motion Analysis) in passive line array SONAR have lower bearing rate and frequency doppler, and are not detected or tracked continuously because of various ocean environments. This is a main reason to effect the TMA performance and it takes a long time to get TMA solutions. We propose the bearing and frequency TMA(BFTMA) using accumulative batch estimation to solve the TMA problem of line array passive SONAR. The accumulative batch estimation structure is based on MLE (Maximum Likelihood Estimation) but used accumulative measurements. The accumulative batch estimation is applied for the BFTMA with nonlinear Kalman filter to estimate the target range, speed and course. Simulation and sea data analysis were carried out to verify the performance and applicability of the proposed techniques.

• 전기전자학회논문지
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• 제23권2호
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• pp.710-715
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• 2019

We consider parameter estimation in distributed systems in which measurements at local nodes are quantized in a non-regular manner, where multiple codewords are mapped into a single local measurement. For the system with non-regular quantization, to ensure a perfect independent encoding at local nodes, a local measurement can be encoded into a set of a great number of codewords which are transmitted to a fusion node where estimation is conducted with enormous computational cost due to the large cardinality of the sets. In this paper, we propose an efficient estimation technique that can handle the non-regular quantized data by efficiently finding the feasible combination of codewords without searching all of the possible combinations. We conduct experiments to show that the proposed estimation performs well with respect to previous novel techniques with a reasonable complexity.

• 전력전자학회논문지
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• 제27권4호
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• pp.332-338
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• 2022

This study proposes a battery state-of-health estimation method by applying a feature extraction technique. The technique that can improve estimation performance is the process of identifying and extracting meaningful data. To apply a data-driven-based aging state estimation method to batteries, health indicators are used as training data. However, limitations occur in extracting health indicators from charge/discharge cycles. This study proposes a deep-learning-based battery state-of-health estimation method that applies feature extraction techniques to compensate for this problem. According to the performance evaluation result of the proposed method, it has a low estimation error of 0.3887% based on an absolute error evaluation method.

• 제어로봇시스템학회논문지
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• 제18권3호
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• pp.285-294
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• 2012

Using bearing measurement only, target motion state is not directly obtained so that TMA (Target Motion Analysis) is needed for this situation. TMA is a nonlinear estimation technique used in passive SONAR systems. Also it is the one of important techniques for underwater combat management systems. TMA can be divided to two parts: batch estimation and sequential estimation. It is preferable to use sequential estimation for reducing computational load as well as adaptively to target maneuvers, batch estimation is still required to attain target initial state vector for convergence of sequential estimation. Selection of batch time interval which depends on observability is critical in TMA performance. Batch estimation in general utilizes predetermined batch time interval. In this paper, we propose a new method called the BTIS (Batch Time Interval and Initial State Estimation). The proposed BTIS estimates target initial status and determines the batch time interval sequentially by using a bank of GMM-TS (Gaussian Mixture Measurement-Track Splitting) filters. The performance of the proposal method is verified by a Monte Carlo simulation study.

• Journal of Astronomy and Space Sciences
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• 제35권4호
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• pp.263-277
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• 2018

This paper presents a vision-based relative pose estimation algorithm and its validation through both numerical and hardware experiments. The algorithm and the hardware system were simultaneously designed considering actual experimental conditions. Two estimation techniques were utilized to estimate relative pose; one was a nonlinear least square method for initial estimation, and the other was an extended Kalman Filter for subsequent on-line estimation. A measurement model of the vision sensor and equations of motion including nonlinear perturbations were utilized in the estimation process. Numerical simulations were performed and analyzed for both the autonomous docking and formation flying scenarios. A configuration of LED-based beacons was designed to avoid measurement singularity, and its structural information was implemented in the estimation algorithm. The proposed algorithm was verified again in the experimental environment by using the Autonomous Spacecraft Test Environment for Rendezvous In proXimity (ASTERIX) facility. Additionally, a laser distance meter was added to the estimation algorithm to improve the relative position estimation accuracy. Throughout this study, the performance required for autonomous docking could be presented by confirming the change in estimation accuracy with respect to the level of measurement error. In addition, hardware experiments confirmed the effectiveness of the suggested algorithm and its applicability to actual tasks in the real world.

• 물과 미래
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• 제27권1호
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• pp.89-99
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• 1994

현재까지 국내의 홍수예측업무는 과거에 수집된 자료집단을 이용한 변수추정에 의하여 시행되고 있으나, 최근 여러 가지 순환추정 알고리즘을 적용한 홍수예측 또는 변수추정에 관한 많은 연구가 이루어지고 있다. 본 논문은 실시간 홍수예측 및 변수추정에 관한 연구로서, 특히 강우-유출모형의 상태 및 매개변수의 동시추정에 관한 추계학적 현상을 고려하였다. 홍수예측에 관한 시스템은 $\phi$ 지수에 의한 유효강우의 산정과 지체효과를 고려한 n개의 비선형 저수지모형에 의한 홍수축적으로 구성하였다. 그리고 변수추정모형과 홍수추적 모형을 상호연계하여 변수를 포함하는 확대 상태-공간모형으로 상태 및 매개변수의 동시추정에 관한 시스템을 구성하였다. 상태-공간모형에 대한 상태 및 변수추정기법으로 GLS 추정과 MAP 추정에 대하여 비교 검토하였다. 모형의 식별을 위한 민감도 분석은 추정변수의 공분산 행렬을 사용하였다.