• Journal of the Korean Society of Manufacturing Process Engineers
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• v.10 no.3
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• pp.33-38
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• 2011

A cubic spline trajectory planner with arc-length parameter is formulated with estimation by summing up to the 3rd order in Taylor's expansion. The PVAJT motion planning is presented to reduce trajectory calculation time at every cycle time of servo control loop so that it is able to generate cubic spline trajectory in real time. This method can be used to more complex spline trajectory. Several case studies are executed with different values of cycle time and sampling time, and showed the advantages of the PVAJT motion planner. A DSP-based motion controller is designed to implement the PVAJT motion planning.

• Industrial Engineering and Management Systems
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• v.13 no.4
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• pp.357-368
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• 2014

Since its birth in 1993, fuzzy time series have seen different classes of models designed and applied, such as fuzzy logic relation and rule-based models. These models have both advantages and disadvantages. The major drawbacks with these two classes of models are the difficulties encountered in identification and analysis of the model. Therefore, there is a strong need to explore new alternatives and this is the objective of this paper. By transforming a fuzzy number to a real number via integrating the inverse of the membership function, new autoregressive models can be developed to fit the observation values of a fuzzy time series. With the new models, the issues of model identification and parameter estimation can be addressed; and trends, seasonalities and multivariate fuzzy time series could also be modeled with ease. In addition, asymptotic behaviors of fuzzy time series can be inspected by means of characteristic equations.

• International Journal of Reliability and Applications
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• v.7 no.1
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• pp.27-39
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• 2006

Many real world cases in material failure analysis do not follow perfectly the normal distribution. Forcing of the normality assumption may lead to inaccurate predictions and poor product quality. We examine the failure process of the internal bond (IB or tensile strength) of medium density fiberboard (MDF). We propose a forced censoring technique that closer fits the lower tails of strength distributions and better estimates extremely smaller percentiles, which may be valuable to continuous quality improvement initiatives. Further analyses are performed to build an accelerated common-shaped Weibull model for different product types using the $JMP^{(R)}$ Survival and Reliability platform. In this paper, a forced censoring technique is implemented for the first time as a software module, using $JMP^{(R)}$ Scripting Language (JSL) to expedite data processing, which is crucial for real-time manufacturing settings. Also, we use JSL to automate the task of fitting an accelerated Weibull model and testing model homogeneity in the shape parameter. Finally, a package script is written to readily provide field engineers customized reporting for model visualization, parameter estimation, and percentile forecasting. Our approach may be more accurate for product conformance evaluation, plus help reduce the cost of destructive testing and data management due to reduced frequency of testing. It may also be valuable for preventing field failure and improved product safety even when destructive testing is not reduced by yielding higher precision intervals at the same confidence level.

• Journal of the Earthquake Engineering Society of Korea
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• v.18 no.1
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• pp.29-36
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• 2014

In industrial facilities sites, the conventional method determining the earthquake magnitude (M) using earthquake ground-motion records is generally not applicable due to the poor quality of data. Therefore, a new methodology is proposed for determining the earthquake magnitude in real-time based on the amplitude measures of the ground-motion acceleration mostly from S-wave packets with the higher signal-to-ratios, given the Vs30 of the site. The amplitude measures include the bracketed cumulative parameters and peak ground acceleration (As). The cumulative parameter is either CAV (Cumulative Absolute Velocity) with 100 SPS (sampling per second) or BSPGA (Bracketed Summation of the PGAs) with 1 SPS. The arithmetic equations to determine the earthquake magnitude are derived from the CAV(BSPGA)-As-M relations. For the application to broad ranges of earthquake magnitude and distance, the multiple relations of CAV(BSPGA)-As-M are derived based on worldwide earthquake records and successfully used to determine the earthquake magnitude with a standard deviation of ${\pm}0.6M$.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.12 no.6
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• pp.609-615
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• 2000

The energy conservation is one of the most important issues in recent years. Especially, the energy conservation through improved control strategies is one of the most highly possible area to be implemented in the near future. The energy conservation of the ice storage system can be accomplished through the improved control strategies. A real time building load prediction algorithm was developed. The expected highest and the lowest outdoor temperature of the next day were used to estimate the next day outdoor temperature profile. The measured dry bulb temperature and the measured building load were used to estimate system parameters by using the on-line weighted recursive least square method. The estimated hourly outdoor temperatures and the estimated hourly system parameters were used to predict the next day hourly building loads. In order to see the effectiveness of the building load prediction algorithm, two different types of building models were selected and analysed. The simulation results show less than 1% in error for the prediction of the next day building loads. Therefore, this algorithm may successfully be used for the development of improved control algorithms of the ice storage system.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.2
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• pp.284-290
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• 2012

This paper addresses a new passive target tracking problem using the range differences measured by cooperative UAVs. In order to solve the range difference based passive target tracking problem within the framework of linear robust state estimation, the uncertain linear measurement model which contains the stochastic parameter uncertainty is derived by using the noisy range difference measurements. To cope with the performance degradation due to the stochastic parameter uncertainty, the recently developed non-conservative robust Kalman filtering technique [1] is applied. For the cruciform formation flying UAVs, the relationship between the target tracking performance and the measurement errors is quantitatively analyzed. The proposed filter has practical advantages over the classical nonlinear filters because, for its recursive linear structure, it can provide satisfactory convergence properties and is suitable for real-time multiple UAVs applications. Through the simulations, the usefulness of the proposed method is demonstrated.

• Communications for Statistical Applications and Methods
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• v.27 no.4
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• pp.413-430
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• 2020

The multiply Type-II hybrid censoring scheme is disadvantaged by an experiment time that is too long. To overcome this limitation, we propose a generalized multiply Type-II hybrid censoring scheme. Some estimators of the scale parameter of the exponential distribution are derived under a generalized multiply Type-II hybrid censoring scheme. First, the maximum likelihood estimator of the scale parameter of the exponential distribution is obtained under the proposed censoring scheme. Second, we obtain the Bayes estimators under different loss functions with a noninformative prior and an informative prior. We approximate the Bayes estimators by Lindleys approximation and the Tierney-Kadane method since the posterior distributions obtained by the two priors are complicated. In addition, the Bayes estimators are obtained by using the Markov Chain Monte Carlo samples. Finally, all proposed estimators are compared in the sense of the mean squared error through the Monte Carlo simulation and applied to real data.

• Journal of Power Electronics
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• v.10 no.5
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• pp.491-497
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• 2010

This paper proposes an estimation algorithm for the electrical parameters of synchronous reluctance motors (SynRMs) by using a synchronous PI current regulator at standstill. In reality, the electrical parameters are only measured or estimated in limited conditions without fully considering the effects of the switching devices, connecting wires, and magnetic saturation. As a result, the acquired electrical parameters are different from the real parameters of the motor drive system. In this paper, the effects of switching devices, connecting wires, and the magnetic saturation are considered by simultaneously using the short pulse and closed loop equations of resistance and synchronous inductances. Therefore, the proposed algorithm can be easily and safely implemented with a reduced measuring time. In addition, it does not need any external or additional measurement equipment, information on the motor's dimensions, and material characteristics as in the case of FEM. Several experimental results verify the effectiveness of the proposed algorithm.

• Journal of the Architectural Institute of Korea Structure & Construction
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• v.36 no.3
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• pp.169-176
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• 2020

The authors developed a nodal network model that simulates the flow of moist air and the thermal behavior of a target area. The nodal network model was enhanced using a parameter estimation technique based on the measured temperature, humidity, and schedule data. However, the nodal model is not good enough for predicting humidity of the target space, having 55.6% of CVRMSE. It is because re-evaporation effect could not be modeled due to uncertain factors in the field measurement. Hence, a data-driven model was introduced using an artificial neural network (ANN). It was found that the data-driven model is suitable for predicting the condensation compared to the nodal model satisfying ASHRAE Guideline with 3.36% of CVRMSE for temprature, relative humidity, and surface temperature on average. The model will be embedded in automated devices for real-time predictive control, to minimize the risk of surface condensation at dressroom in an apartment housing.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.54 no.6
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• pp.293-305
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• 2005

This paper describes an improved Prony method in its speed, accuracy and reliability by efficiently determining the optimal sampling interval with use of DFT (discrete Fourier transformation). In the Prony method the computation time is dominated by the size of the linear prediction matrix, which is given by the number of data times the modeling order The size of the matrix in a general Prony method becomes large because of large number of data and so does the computation time. It is found that the Prony method produces satisfactory results when SNR is greater than three. The maximum sampling interval resulting minimum computation time is determined using the fact that the spectrum in DFT is inversely proportional to sampling interval. Also the process of computing the modes is made efficient by applying Hessenberg method to the companion matrix with complex shift and computing selectively only the dominant modes of interest. The proposed method is tested against the 2003 KEPCO system and found to be efficient and reliable. The proposed method may play a key role in monitoring in real time low frequency oscillations of power systems .