• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2006.06b
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• pp.67-74
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• 2006

In this paper, an adaptive neural network controller and its application to automatic berthing control of ship is presented. The neural network controller is trained online using adaptive interaction technique without any teaching data and off-line training phase. Firstly, the neural networks used to control rudder and propeller during automatic berthing process are presented. Finally, computer simulations of automatic ship berthing are carried out to verify the proposed controller with and without the influence of wind disturbance and measurement noise.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2000.04a
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• pp.56-63
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• 2000

Abstract - In this paper, an adaptive mechanism based on immune algorithm is designed and it is applied for the autonomous guided vehicle(AGV) driving. When the immune algorithm is applied to the PID controller, there exists the case that the plant is damaged due to the abrupt change of PID parameters since the parameters are adjusted almost randomly. To solve this problem, a neural network is used to model the plant and the parameter tuning of the model is performed by the immune algorithm. After the PID parameters are determined in this off-line manner, these gains are then applied to the plant for the on-line control using immune adaptive algorithm. Moreover, even though the neural network model may not be accurate enough intially, the weighting parameters are adjusted to be accurate through the on-line fine tuning. The computer simulation for the control of steering and speed of AGV is performed. The results show that the proposed controller has better performances than other conventional controllers.

• Journal of Advanced Navigation Technology
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• v.15 no.4
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• pp.571-577
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• 2011

This paper presents a novel balanced filter design based on a metamaterial structure applicable to differential-mode excitation. The metamaterial structure is based on a unit-cell which under a differential-mode excitation behaves like composite right/left-handed(CRLH) metamaterial with filter characteristics. In contrast, the metamaterial unit-cell is below cut-off under a common-mode excitation. Experimental results are used to verify the proposed metamaterial's differential-mode characteristics. The metamaterial is fabricated with a balanced filter design resulting in an operating frequency range of 960~1000 MHz with a insertion loss of 4.1 dB.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2006.10a
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• pp.176-183
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• 2006

A novel intelligent anti-collision decision-making supporting system is addressed in this paper. To obtain precise anti-collision information capability, an innovative neurofuzzy network is proposed and applied. A fuzzy set interpretation is incorporated into the network design to handle imprecise information. A neural network architecture is used to train the parameters of the Fuzzy Inference System (FIS). The learning process is based on a hybrid learning algorithm and off-line training data. The training data are obtained by trial manoeuvre. This neurofuzzy network can be considered to be a self-learning system with the ability to learn new information adaptively without forgetting old knowledge. This supporting system can decrease ship operators' burden to deal with bridge data and help them to make a precise anti-collision decision.

• Proceedings of the KIEE Conference
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• 2003.07d
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• pp.2420-2422
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• 2003

In this paper, two Fuzzy Logics for path planning of an autonomous mobile robot are proposed. If a target point is given, such problems regarding the velocity and object recognition are closely related with path to which the mobile robot navigates. Therefore, to ensure safety navigation of the mobile robot for two fuzzy logic parts, path planning considering the surrounding environment was performed in this paper. First, feature points for local and global path are determined by utilizing Cell Decomposition off-line computation. Second, the on-line robot using two Fuzzy Logics navigates around path when it tracks the feature points. We demonstrated optimized path planning only for local path using object recognition fuzzy logic corresponds to domestic situation. Furthermore, when navigating, the robot uses fuzzy logic for velocity and target angle. The proposed algorithms for path planning has been implemented and tested with pioneer-dxe mobile robot.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2003.05a
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• pp.265-272
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• 2003

Off-line ship chartering is done nearly through(by) the brokers. Because of the international scale of chartering marker, brokers spend too much times and costs on searching the most appropriate product which the consumers want. In this research, we propose the on-line Charter Product Categorization Model to search the products efficiently in the Cyber Chartering System. This Model will make concerned parties of the ship chartering to get efficient and unific product information. and to select the most appropriate product. In this research, we classified the ship chartering products into categories of cargo, ship type, and sea routes, and formed the definition of mutual relation of each products. Moreover we verified that this classification is necessary to search the products by the product searching experiment.

• Journal of Korean Port Research
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• v.14 no.2
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• pp.187-197
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• 2000

In this paper, an adaptive mechanism based on immune algorithm is designed and it is applied to the driving control of the autonomous guided vehicle(AGV). When the immune algorithm is applied to the PID controller, there exists the case that the plant is damaged by the abrupt change of PID parameters since the parameters are adjusted almost randomly. To solve this problem, a neural network used to model the plant and the parameter tuning of the model is performed by the immune algorithm. After the PID parameters are determined through this off-line manner, these parameters are then applied to the plant for the on-line control using immune adaptive algorithm. Moreover, even though the neural network model may not be accurate enough initially, the weighting parameters are adjusted more accurately through the on-line fine tuning. The experiment for the control of steering and speed of AGV is performed. The results show that the proposed controller provides better performances than other conventional controllers.

• Journal of the Korean Institute of Navigation
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• v.25 no.2
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• pp.131-136
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• 2001

A new analysis method of lumped-element directional coupler for CATV was proposed, where the even-and odd-mode theory for a symmetrical coupled-line directional coupler was applied to a transformer-type directional coupler. In addition, the tap-offs were analyzed by the proposed theory, which are widely used in CATV (Cable Television) systems. By comparing the calculated results for S-parameters results to the measured ones using only the even-and odd-mode reflection coefficients, the validity of the proposed analysis method was confirmed. Then, it was clearly shown that the tap-off has very wide bandwidth from 5 MHz to 4,000 MHz by adopting the proposed theory.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2004.04a
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• pp.49-54
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• 2004

Ubiquitous computing support to use various informations through any machine which can connect the computer in any where and any time. Recently barcode and RFID which is improved business model to store large scale information and certify security in on- and off-line internet technology is applied the credit curd and payment service and so on However this technology has serious problem that RFID In this paper, we investigate method used example of 2D barcode and RFID and compare and analysis characteristics of recent technology to solve former problem in Ubiquitous environment.

• Journal of Navigation and Port Research
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• v.34 no.2
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• pp.117-122
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• 2010

Since fuzzy controllers are nonlinear, it is more difficult to set the controller gains and to analyse the stability compared to conventional PID controllers. This paper proposes a fuzzy PD+I controller for tracking control which uses a linear fuzzy inference(product-sum-gravity) method based on a conventional linear PID controller. In this scheme the fuzzy PD+I controller works similar to the control performance as the linear PD plus I(PD+I) controller. Thus it is possible to analyse and design an fuzzy PD+I controller for given systems based on a linear fuzzy PD controller. The scaling factors tuning scheme, another topic of fuzzy controller design procedure, is also introduced in order to fine performance of the fuzzy PD+I controller. The scaling factors are adjusted by a real-coded genetic algorithm(RCGA) in off-line. The simulation results show the effectiveness of the proposed fuzzy PD+I controller for tracking control problems by comparing with the conventional PID controllers.