• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.13 no.8
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• pp.682-691
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• 2001

Most of radiant floor heating systems are operated in the intermittent heating mode in Korea. The application possibility of predictive suboptimal control for Koran residential house was investigated by computer simulation and experiment. For this study, TRNSYS program was used and an experimental facility consisting of tow rooms ($3\times4.4\times2.8 m$) identical in construction was built. The facility enabled simultaneous comparison of two different control method. And real multi residential hose was investigated. Results showed that outdoor air temperature prediction control was superior to the conventional control for radiant floor heating system operated in the intermittent heating mode. New control system resulted in good thermal environment and les energy consumption.

• Journal of the Korean Society for Railway
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• v.9 no.6 s.37
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• pp.732-738
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• 2006

This research provides a scheme for Highly Accelerated Stress Test that is necessary to demonstrate reliability prediction of Korean Rapid Transit Railway Train Control System sub-equipment, which is calculated by a relevant standard for failure rate prediction of electronic products. Although determining failure information generated in the process of trial running by statistic analysis is widely accepted as a measure of confirmation for reliability prediction, this research suggests the modeling for System Life Test determined by accelerating stress factors as a measure of confirmation for reliability prediction of sub-equipment unit that is generated ahead of a trial running in System Life Cycle. Consequently, the research demonstrates sub-equipment unit reliability test, which is based on the model derived from Accelerated Stress Test, according to accuracy level and the number of samples, and conducts an official experiment by making out a reliability test procedure sheet based on test time as well.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.652-657
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• 2004

As the real-time multimedia applications through Internet increase, the bandwidth available to TCP connections is oppressed by the UDP traffic, result in the performance of overall system is extremely deteriorated. Therefore, developing a new transmission protocol is necessary. The TCP-friendly algorithm is an example meeting this necessity. The TCP-friendly (TFRC) is an UDP-based protocol that controls the transmission rate based on the available round transmission time (RTT) and the packet loss rate (PLR). In the data transmission processing, transmission rate is determined based on the conditions of the previous transmission period. If the one-step ahead predicted values of the control factors are available, the performance will be improved significantly. This paper proposes a prediction model of transmission rate control factors that will be used for the transmission rate control, which improves the performance of the networks. The model developed through this research is predicting one-step ahead variables of RTT and PLR. A multiplayer perceptron neural network is used as the prediction model and Levenberg-Marquardt algorithm is used for the training. The values of RTT and PLR were collected using TFRC protocol in the real system. The obtained prediction model is validated using new data set and the results show that the obtained model predicts the factors accurately.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.1
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• pp.104-111
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• 2000

A fuzzy logic Run-by-Run(RbR) controller and an in -line wafer characteristics prediction scheme for the rapid thermal processing system have been developed for the study of process repeatability. The fuzzy logic RbR controller provides a framework for controlling a process which is subject to disturbances such as shifts and drifts as a normal part of its operation. The fuzzy logic RbR controller combines the advantages of both fuzzy logic and feedback control. It has two components : fuzzy logic diagnostic system and model modification system. At first, a neural network model is constructed with the I/O data collected during the designed experiments. The wafer state after each run is assessed by the fuzzy logic diagnostic system with featuring step. The model modification system updates the existing neural network process model in case of process shift or drift, and then select a new recipe based on the updated model using genetic algorithm. After this procedure, wafer characteristics are predicted from the in-line wafer characteristics prediction model with principal component analysis. The fuzzy logic RbR controller has been applied to the control of Titanium SALICIDE process. After completing all of the above, it follows that: 1) the fuzzy logic RbR controller can compensate the process draft, and 2) the in-line wafer characteristics prediction scheme can reduce the measurement cost and time.

• Journal of the Korean Society of Safety
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• v.21 no.3 s.75
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• pp.114-121
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• 2006

As one of the serviceability limit states, the prediction and control of crack width in reinforced concrete bridges or PSC bridges are very important for the design of durable structures. However, the current bridge design specifications do not provide quantitative information for the prediction and control of crack width affected by the initiation and propagation of corrosion. Considering life span of concrete bridges, an improved control equation about the crack width affected by time-dependent general corrosion is proposed. The developed corrosion and crack width control models can be used for the design and the maintenance of prestressed and non-prestressed reinforcements by varying time, w/c, cover depth, and geometries of the sections. It can also help the rational criteria for the quantitative management and the prediction of remaining life of concrete structures.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.9
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• pp.906-908
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• 2009

AVI (Automatic Vision Inspection) systems automatically detect defect features and measure their sizes via camera vision. It is important to predict the performance of an AVI to meet customer's specification in advance. Also the prediction can indicate the level of current performance of an AVI system. In this paper, we propose a statistical method for prediction of false alarm rate regarding inconsistency of defect size measurement process. For this purpose, only simple experiments are needed to measure the defect sizes for certain number of times. The statistical features from the experiment are utilized in the prediction process. Therefore, the proposed method is swift and easy to implement and use. The experiment shows a close prediction compared to manual inspection results.

• Journal of the Korean Solar Energy Society
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• v.39 no.5
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• pp.41-52
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• 2019

The purpose of the work is to develop a simple solar irradiance prediction model using a deep learning method, the LSTM (long term short term memory). Other than existing prediction models, the proposed one uses only the cloudiness among the information forecasted from the national meterological forecast center. The future cloudiness is generally announced with four categories and for three-hour intervals. In this work, a daily irradiance pattern is used as an input vector to the LSTM together with that cloudiness information. The proposed model showed an error of 5% for learning and 30% for prediction. This level of error has lower influence on the load prediction in typical building cases.

• 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.

• International Journal of Control, Automation, and Systems
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• v.3 no.4
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• pp.509-523
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• 2005

We are developing a novel framework, PRIDE (PRediction In Dynamic Environments), to perform moving object prediction (MOP) for autonomous ground vehicles. The underlying concept is based upon a multi-resolutional, hierarchical approach which incorporates multiple prediction algorithms into a single, unifying framework. The lower levels of the framework utilize estimation-theoretic short-term predictions while the upper levels utilize a probabilistic prediction approach based on situation recognition with an underlying cost model. The estimation-theoretic short-term prediction is via an extended Kalman filter-based algorithm using sensor data to predict the future location of moving objects with an associated confidence measure. The proposed estimation-theoretic approach does not incorporate a priori knowledge such as road networks and traffic signage and assumes uninfluenced constant trajectory and is thus suited for short-term prediction in both on-road and off-road driving. In this article, we analyze the complementary role played by vehicle kinematic models in such short-term prediction of moving objects. In particular, the importance of vehicle process models and their effect on predicting the positions and orientations of moving objects for autonomous ground vehicle navigation are examined. We present results using field data obtained from different autonomous ground vehicles operating in outdoor environments.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2003.05a
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• pp.738-741
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• 2003

In general, the essential requirement for cruisers or car ferries is the reduction in noise to ensure high quality and comfort. Recently, the Ro-Ro Passengers Ferry (ROPAX) was built in Hyundai Heavy Industries. In order to minimize the noise levels, careful attention have to De paid by the special committee of experts from the initial design stage to the sea trial. Proper countermeasures, considering the characteristics of sources and receiver spaces, were applied from the noise prediction and various experiment results. Finally, this ship was successfully delivered with excellent noise properties. This paper describes the procedure of noise analysis, the countermeasures of noise control, and the measurement results of the sea trial. Onboard noise analysis had been carried out by statistical energy analysis program and outdoor noise prediction program based on ISO9614. The prediction results are in good agreements with the measurement results. The technology to minimize the noise levels for cruisers or car ferries has been established throughout the construction of this ship.