• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.754-759
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• 1993

An adaptive model predictive control (AMPC) strategy using auto-regression moving-average (ARMA) models is presented. The characteristic features of this methodology are the small computer memory requirement, high computational speed, robustness, and easy handling of nonlinear and time varying MIMO systems. Since the process dynamic behaviors are expressed by ARMA models, the model parameter adaptation is simple and fast to converge. The recursive least square (RLS) method with exponential forgetting is used to trace the process model parameters assuming the process is slowly time varying. The control performance of the AMPC is verified by both comparative simulation and experimental studies on distillation column control.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2002.10a
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• pp.567-574
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• 2002

새로운 자유격자 관사를 이용한 점별 계산법을 제안한다 이동 최소 자승법을 이용한 기저의 생성과 기저의 근사적 미분을 동시에 구해내는 자유격자 근사를 유도하여, 직접 점별 계산법을 고안하였다. 기존의 자유 격자 법에서는 기저의 직접 미분을 사용하므로 높은 계산 비용이 필요하지만, 이 논문에서 제안된 방법은 기저의 생성과 동시에 기저의 근사적 미분을 구하게 된다. 또한 기존의 방법에서 필요하였던, 창 함수(window function)의 미분가능성을 연속성으로 대치할 수 있으므로, 주어진 문제에 따라 다양한 창 함수를 이용할 수 있다. 기저의 재생성과 interpolation의 수렴성을 소개하고, 수치 예제로서, Poisson 문제를 통해 이 방법의 유효함을 보인다.

• The Journal of the Acoustical Society of Korea
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• v.35 no.4
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• pp.310-318
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• 2016

This study deals with a method to localize a noise source occuring in a marine vehicle in a 3D environment. Even when access to the noise source is limited for a marine vehicle, such as a ship or a submarine in operation, the signal received on a hydrophone located elsewhere contains Doppler effected noise by moving relatively. This study suggests noise localization algorithm in 3D based on Doppler effect by moving marine vehicle. Using a known source mounted on the vehicle, the noise source was estimated by reducing the range of Doppler center and closest point of approach via the least square method. The algorithm was verified through various simulations and it was shown that the noise could be localized in 3D based on Doppler effect by employing two fixed hydrophones located at the vehicle's exterior points and a known reference signal generator located somewhere on the vehicle.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.35 no.5
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• pp.193-198
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• 1986

In this paper, 1-168 hours ahead load prediction algorithm is developed for power system economic weekly operation. Total load is composed of three components, which are base load, week load and weather-sensitive load. Base load and week load are predicted by moving average and exponential smoothing method, respectively. The days of moving average and smoothing constant are optimally determined. Weather-sensitive load is modeled by linear form. The paramiters of weather load model are estimated by exponentially weighted recursive least square method. The load prediction of special day is very tedious, difficult and remains many problems which should be improved. Test results are given for the day of different types using the actual load data of KEPCO.

• Journal of Information Technology Applications and Management
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• v.12 no.1
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• pp.141-155
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• 2005

It is very important that sellers provide reasonable reserve prices for auction items in internet auction systems. Recently, an agent has been proposed to generate reserve prices automatically based on the case similarity of information retrieval theory and the moving average of time series analysis. However, one problem of the previous approaches is that the recent trend of auction prices is not well reflected on the generated reserve prices, because it simply provides the bid price of the most similar item or an average price of some similar items using the past auction data. In this paper. in order to overcome the problem. we propose a method that generates reserve prices based on the moving average. the exponential smoothing, and the least square of time series analysis. Through performance experiments. we show that the successful bid rate of the new method can be increased by preventing sellers from making unreasonable reserve prices compared with the previous methods.

• Computers and Concrete
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• v.23 no.6
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• pp.433-444
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• 2019

As rice husk ash (RHA) is not produced in controlled manufacturing process like cement, its properties vary significantly even within the same lot. In fact, properties of Rice Husk Ash Based Concrete (RHABC) are largely dictated by uncertainty leading to huge deviations from their expected values. This paper proposes a Robust Cost Optimization (RCO) procedure for RHABC, which minimizes such unwanted deviation due to uncertainty and provides guarantee of achieving desired strength and workability with least possible cost. The RCO simultaneously minimizes cost of RHABC production and its deviation considering feasibility of attaining desired strength and workability in presence of uncertainty. RHA related properties have been modeled as uncertain-but-bounded type as associated probability density function is not available. Metamodeling technique is adopted in this work for generating explicit expressions of constraint functions required for formulation of RCO. In doing so, the Moving Least Squares Method is explored in place of conventional Least Square Method (LSM) to ensure accuracy of the RCO. The efficiency by the proposed MLSM based RCO is validated by experimental studies. The error by the LSM and accuracy by the MLSM predictions are clearly envisaged from the test results. The experimental results show good agreement with the proposed MLSM based RCO predicted mix properties. The present RCO procedure yields RHABC mixes which is almost insensitive to uncertainty (i.e., robust solution) with nominal deviation from experimental mean values. At the same time, desired reliability of satisfying the constraints is achieved with marginal increment in cost.

• Journal of Ocean Engineering and Technology
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• v.28 no.2
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• pp.93-101
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• 2014

In general, particle simulation methods such as the MPS(Moving Particle Simulation) or SPH(Smoothed Particle Hydrodynamics) methods have some serious drawbacks for pressure solutions. The pressure field shows spurious high fluctuations both temporally and spatially. It is well known that pressure fluctuation primarily occurs because of the numerical approximation of the partial differential operators. The MPS and SPH methods employ a pre-defined kernel function in the approximation of the gradient and Laplacian operators. Because this kernel function is constructed artificially, an accurate solution cannot be guaranteed, especially when the distribution of particles is irregular. In this paper, we propose a particle simulation method based on the moving least-square technique for solving the partial differential operators using a Taylor-series expansion. The developed method was applied to the hydro-static pressure and dam-broken problems to validate it.

• Communications for Statistical Applications and Methods
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• v.25 no.4
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• pp.431-442
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• 2018

This paper highlights the computational explosion issues in the autoregressive moving average approach of frequency estimation of sinusoidal data with a large sample size. A new algorithm is proposed to circumvent the computational explosion difficulty in the conditional least-square estimation method. Notice that sinusoidal pattern can be generated by a non-invertible non-stationary autoregressive moving average (ARMA) model. The computational explosion is shown to be closely related to the non-invertibility of the equivalent ARMA model. Simulation studies illustrate the computational explosion phenomenon and show that the proposed algorithm can efficiently overcome computational explosion difficulty. Real data example of sunspot number is provided to illustrate the application of the proposed algorithm to the time series data exhibiting sinusoidal pattern.

• Journal of information and communication convergence engineering
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• v.18 no.2
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• pp.88-93
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• 2020

The IEEE 802.11p-based wireless access in vehicular environments (WAVE) [1] communication is a method used exclusively for wireless communication on the road. This technique enables information sharing not only among moving vehicles but also between vehicles and infrastructure [2]. As part of WAVE communication, data is transmitted to and from vehicles in motion; in this case, it is difficult to determine the channel accurately in an outdoor environment owing to the Doppler shift [3]. This paper proposes a new channel estimation scheme for enhancing the reception performance of the IEEE 802.11p-based WAVE system. The proposed technique obtains the initial channel value by estimating the least square in the time domain by inserting a pilot signal for channel estimation into the IEEE 802.11p virtual subcarrier. Subsequently, a least mean square algorithm is applied to the initial channel value to update the estimated channel value. The simulation results obtained using the proposed channel estimation technique confirm its remarkable efficiency.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.15 no.11 s.104
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• pp.1303-1310
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• 2005

Stabilization error of target aiming systems mounted on moving vehicles is an important performance because the error directly affects hit Probability. In a heavy load targetaiming system, the disturbance torque comes from mass unbalance and linear acceleration is a main source of stabilization error. This study suggests an experimental design method of disturbance feedforward compensation control to improve the stabilization performance of heavy load target aiming systems. The filtered_x least square(FxLMS) algorithm is used to estimate the compensator coefficients adaptively. The proposed control is applied to a simple experimental set-up which simulates dynamic characteristics of a real target aiming system. The feasibility of the proposedtechnique is illustrated, along with results of experiments.