• Journal of Institute of Control, Robotics and Systems
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• v.17 no.4
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• pp.321-327
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• 2011

This paper proposes an equipment and an algorithm for modeling the magnetic force of electromagnets in magnetic levitation systems. We assume that the magnetic force model is represented in terms of a 2D lookup table. The 2D lookup table is constructed by applying noncausal filtering and interpolation to data measured by the proposed modeling equipment. The proposed modeling equipment is designed such that it can measure the magnetic force exerted on the levitation object while it changes the voltage applied to the electromagnet and position of the levitation object. The algorithm of making a 2D lookup table has two stages. The data measured by the proposed modeling equipment is smoothed by a noncausal filter and then the 2D lookup table is obtained by interpolating filtered data. The proposed modeling method has advantages of time-saving, model consistency, and chance of automation for mass production. We show the validity of proposed method through control experiments.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.2
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• pp.298-305
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• 2010

In this paper, a new algorithm of optimal Volt/Var Control is proposed using Volt/Var control for the Distribution Automation System (DAS) with Distributed Generation (DG) based on the modeling of the distributed load and the distributed current. In the proposed, algorithm based on the modeling of the distributed load and the distributed current are estimated from constants of four terminals using the measurement of the current and power factor from a Feeder Remote Terminal Unit (FRTU) and DG data from RTU for DG. For the optimal Volt/Var Control, the gradient method is applied to find optimal solution for tap, capacity and power control of OLTC (On-Load Tap Changers), SVR (Step Voltage Regulator), PC (Power Condenser) and DG (Distributed Generation). In the case studies, the estimation and control of the voltages have been testified in a radial distribution system with DG using matlab program.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.49 no.5
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• pp.241-248
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• 2000

Until now, all of the port goods are transported manually by container transporter in the port. Recently there are a lot of studies about unmanned vehicle driven automatically. In terms of the vehicle automation, the control of steering and velocity on vehicle systems is very important part in container transporter. In common sense, vehicle systems have lots of nonlinear parameters so we have many difficulties in designing the optimal controller of them. In this paper, we present a design of the TDOF PID controller using a hybrid schematic algorithm to control the steering system optimally. We used the single-track model to pre-test the designed controller before appling to AGV. We also used the ES(evolutionary strategy) and SA(simulated annealing) algorithms to construct the hybrid tuning algorithm for parameters of controller. Finally, we had the computer simulation to verify that our designed controller has better performance than the other one.

• Journal of Electrical Engineering and Technology
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• v.13 no.4
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• pp.1740-1751
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• 2018

This paper proposes a novel fault tolerant tracking control (FTTC) scheme for a class of nonlinear systems with actuator failures based on the policy iteration (PI) algorithm and the adaptive fault observer. The estimated actuator failure from an adaptive fault observer is utilized to construct an improved performance index function that reflects the failure, regulation and control simultaneously. With the help of the proper performance index function, the FTTC problem can be transformed into an optimal control problem. The fault tolerant tracking controller is composed of the desired controller and the approximated optimal feedback one. The desired controller is developed to maintain the desired tracking performance at the steady-state, and the approximated optimal feedback controller is designed to stabilize the tracking error dynamics in an optimal manner. By establishing a critic neural network, the PI algorithm is utilized to solve the Hamilton-Jacobi-Bellman equation, and then the approximated optimal feedback controller can be derived. Based on Lyapunov technique, the uniform ultimate boundedness of the closed-loop system is proven. The proposed FTTC scheme is applied to reconfigurable manipulators with two degree of freedoms in order to test the effectiveness via numerical simulation.

• Proceedings of the Korea Institute of Fire Science and Engineering Conference
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• 1997.11a
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• pp.252-259
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• 1997

A method to automate hazard analysis of chemical plants is proposed in this paper. The proposed system is composed of three knowledge bases - unit knowledge base, organizational knowledge base and material knowledge base, and three hazard analysis algorithms - deviation, malfunction and accident analysis algorithm. Hazard analysis inference procedure is developed based on the actual hazard analysis procedures and accident development sequence. The proposed algorithm can perform hazard analysis in two methods and represent all conceivable types of accidents using accident analysis algorithm. In addition, it provides intermediate steps in the accident propagation, and enables the analysis result to give a useful information to hazard assessment. The proposed method is successfully demonstrated by being applied to diammonium phosphate manufacturing process. A system to automate hazard analysis is developed by using the suggested method. The developed system is expected to be useful in finding the propagation path of a fault or the cause of a malfunction as it is capable to approach causes of faults and malfunctions simultaneously.

• Journal of Sensor Science and Technology
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• v.28 no.3
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• pp.164-170
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• 2019

In this paper, a lane detection and tracking algorithm based on vision sensors and employing a robust filter for inner edge detection is proposed for developing a lane departure warning system (LDWS). The lateral offset value was precisely calculated by applying the proposed filter for inner edge detection in the region of interest. The proposed algorithm was subsequently compared with an existing algorithm having lateral offset-based warning alarm occurrence time, and an average error of approximately 15ms was observed. Tests were also conducted to verify whether a warning alarm is generated when a driver departs from a lane, and an average accuracy of approximately 94% was observed. Additionally, the proposed LDWS was implemented as an embedded system, mounted on a test vehicle, and was made to travel for approximately 100km for obtaining experimental results. Obtained results indicate that the average lane detection rates at day time and night time are approximately 97% and 96%, respectively. Furthermore, the processing time of the embedded system is found to be approximately 12fps.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.404-406
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• 2021

In modern society, artificial intelligence and automation are being applied in various fields due to the development of the 4th industrial revolution and IoT technology. In particular, systems with a high proportion of image processing, such as automated processes, intelligent CCTV, medical industry, robots, and drones, are susceptible to external factors noise. In this paper, we propose a digital filter based on noise estimation and weights to reconstruct an image in a complex noise environment. The proposed algorithm classifies the types of noise using noise judgment, and determines the noise level of the filtering mask to switch the filtering process to obtain the final output. In order to verify the performance of the proposed algorithm, simulation was conducted, compared with the existing filter algorithm, and the results were analyzed.

• Journal of the Korean Society of Industry Convergence
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• v.27 no.2_2
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• pp.333-341
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• 2024

The current public survey performance review extracts samples according to the set screening ratio, and examines the extracted samples to determine the suitability or inadequacy of the survey performance. The examiner directly judges the survey performance submitted by the performer, and extracts it in consideration of various field conditions and topography for each subject. However, it is necessary to secure fairness in the examination as it is extracted with different extraction methods for each subject and the judgment of the examiner. Accordingly, in order to automate sampling for public survey performance review, the detailed sampling criteria of the reviewer were investigated to prepare a volume calculation table, and the automation of sampling using Python was studied. In addition, by reviewing items that can and cannot be automated, the application of the automated decision tree algorithm of sampling was reviewed.

• The Journal of Engineering Geology
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• v.27 no.4
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• pp.367-376
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• 2017

Recently, tunneling under the seabed is becoming increasingly common in many countries. In Korea, there are proposals to tunnel from the mainland to Jeju Island. Safe construction requires geologic structures such as faults to be characterized during the design and construction phase; however, unlike on land, such structures are difficult to survey seabed. This study aims to develop an algorithm that uses geostatistics to automatically derive large-scale geological structures on the seabed. The most important considerations in this method are the optimal size of the moving window, the optimal type of spatial statistics, and determination of the optimal percentile standard. Finally, the optimal analysis algorithm was developed using the R program, which comprehensibly presents variations in spatial statistics. The program allows the type and percentile standard of spatial statistics to be specified by the user, thus enabling an analysis of the geological structure according to variations in spatial statistics. The geotechnical defense-training algorithm shows that a large, linear geological lineament is best visualized using a $3{\times}3$ moving window and a 10% upper standard based on the moving variance value and fractile. In particular, setting the fractile criterion to the upper 0.5% almost entirely eliminates the error values from the contour image.

• Korean Journal of Construction Engineering and Management
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• v.5 no.2 s.18
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• pp.90-105
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• 2004

Machines for crack sealing automation have been continually developed since the early 1990's because of the effectiveness of crack sealing that would be able to improve safety, quality and productivity. It has been considered challenging problem to detect crack network in pavement which includes noise (oil marks, skid marks, previously sealed cracks and inherent noise). Moreover, it is required to develop crack network mapping and modeling algorithm in order to accurately inject sealant along to the middle of cut crack network. The primary objective of this study is to propose machine vision algorithms (digital image processing algorithm and path planning algorithm) for fully automated pavement crack sealing. It is anticipated that the effective use of the proposed machine vision algorithms would be able to reduce error rate in image processing for detecting, mapping and modeling crack network as well as improving quality and productivity compared to existing vision algorithms.