• The Journal of the Korea institute of electronic communication sciences
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• v.12 no.5
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• pp.763-770
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• 2017

A radome mounted on the front of an aircraft can cause refraction errors for various reasons that occur during maneuver in seeking and tracking a target. This refraction error means that the microwave seeker is detecting apparent target. An Interactive Multiple Model (IMM) algorithm is applied to estimate radome slope mounted on an aircraft in 3D space. However, even though the parameter of uncertain system model such as radome slope can be estimated, the estimated performance can not be guaranteed when it exceeds the range of the predicted value. In this paper, we propose a method to update the predicted value by using the radome slope as the mode parameter of the IMM algorithm, and confirm the radome slope estimation performance of the proposed method.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.8
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• pp.3391-3397
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• 2011

These excavators have been widely used due to their flexibility in handing various tasks via simple changes of their attachments. Since the performance of manually-operated excavators heavily depend on the operators' skill level, there is a strong need for developing automatic excavators in the industry. In order to achieve such goals, exiting approaches have studied direct modification of existing hydraulic systems in the excavator for feed back control of each link. This paper presents a miniaturized automatic excavator that can be used for the development and demonstration of advanced control algorithm for excavators under a safer environment with reduced cost. Two PCs were installed and connected to the excavator through wireless communications for its control and monitoring. Tracking control of each link using a time varying sliding mode controller was performed through experiments on the developed system to demonstrate its ability.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.8 no.4
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• pp.270-274
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• 2015

We suggest that HSV Color Space may be used to detect a vehicle detecting system at nighttime. It is essential that a licence plate should be extracted when a vehicle is under surveillance. To do so, a licence plate may be enlarged to certain size after the aimed vehicle is taken picture from a distance by using Pan-Tilt-Zoom Camera. Either Mean-Shift or Optical Flow Algorithm is generally used for the purpose of a vehicle detection and trace, even though those algorithms have tendency to have difficulty in detection and trace a vehicle at night. By utilizing the fact that a headlight or taillight of a vehicle stands out when an input image is converted in to HSV Color Space, we are able to achieve improvement on those algorithms for the vehicle detection and trace. In this paper, we have shown that at night, the suggested method is efficient enough to detect a vehicle 93.9% from the front and 97.7% from the back.

• Journal of Internet Computing and Services
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• v.11 no.4
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• pp.23-32
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• 2010

In this paper, we first propose the security enhancing of authentication protocol for Hash based RFID tag, and then a digital Codec for RFID tag is designed based on the proposed authentication protocol. The protocol is based on a three-way challenge response authentication protocol between the tags and a back-end server. In order to realize a secure cryptographic authentication mechanism, we modify three types of the protocol packets which defined in the ISO/IEC 18000-3 standard. Thus active attacks such as the Man-in-the-middle and Replay attacks can be easily protected. In order to verify effectiveness of the proposed protocol, a digital Codec for RFID tag is designed using Verilog HDL, and also synthesized using Synopsys Design Compiler with Hynix $0.25\;{\mu}m$ standard-cell library. Through security analysis and comparison result, we will show that the proposed scheme has better performance in user data confidentiality, tag anonymity, Man-in-the-middle attack prevention, replay attack, forgery resistance and location tracking.

• Journal of Power Electronics
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• v.4 no.1
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• pp.28-38
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• 2004

In this paper, the position control of a detuned indirect field oriented control (IFOC) induction motor drive is studied. A proposed Simple-Neuro-Controllers (SNCs) are designed and analyzed to achieve high-dynamic performance both in the position command tracking and load regulation characteristics for robotic applications. The proposed SNCs are trained on-line based on the back propagation algorithm with a modified error function. Four SNCs are developed for position, speed and ｄ-ｑ axes stator currents respectively. Also, a synchronous proportional plus integral-derivative (PI-D) two-degree-of-freedom (2DOF) position controller and PI-D speed controller are designed for an ideal IFOC induction motor drive with the desired dynamic response. The performance of the proposed SNCs and synchronous PI-D 2DOF position controllers for detuned field oriented induction motor servo drive is investigated. Simulation results show that the proposed SNCs controllers provide high-performance dynamic characteristics which are robust with regard to motor parameter variations and external load disturbance. Furthermore, comparing the SNC position controller with the synchronous PI-D 2DOF position controller demonstrates the superiority of the proposed SNCs controllers due to attain a robust control performance for IFOC induction motor servo drive system.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.2
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• pp.168-177
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• 2008

Path finding is a key element in the navigation of a mobile robot. To find a path, robot should know their position exactly, since the position error exposes a robot to many dangerous conditions. It could make a robot move to a wrong direction so that it may have damage by collision by the surrounding obstacles. We propose a method obtaining an accurate robot position. The localization of a mobile robot in its working environment performs by using a vision system and Virtual Reality Modeling Language(VRML). The robot identifies landmarks located in the environment. An image processing and neural network pattern matching techniques have been applied to find location of the robot. After the self-positioning procedure, the 2-D scene of the vision is overlaid onto a VRML scene. This paper describes how to realize the self-positioning, and shows the overlay between the 2-D and VRML scenes. The suggested method defines a robot's path successfully. An experiment using the suggested algorithm apply to a mobile robot has been performed and the result shows a good path tracking.

• Journal of Institute of Control, Robotics and Systems
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• v.4 no.3
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• pp.321-328
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• 1998

When we control the level of the steam generator in the nuclear power plants, a swell and shrink arises from many disturbances such as feed water rate, feed water temperature, main steam flow rate, and coolant temperature. If we use the conventional type of PI controller in this system, we will not have stability during controlling at lower power, the removal function of disturbances, and a load follow-up control effectively. In this paper, we study the application of a 2-Degree of Freedom(2-DOF) PID controller to the level control of the steam. generator of nuclear power plants through the simulation and the experimental steam generator. We use the parameters $\alpha$, $\beta$, $\gamma$ of the 2-DOF PID controller for the removal of disturbances and the parameters Kp,Ti,Td of the conventional type of PID controller for controlling setpoint. The back-propagation learning algorithm of neural network is used for tuning the 2-DOF PID controller. We can find satisfactory results of the removal of the disturbances and the tracking function in the change of setpoint through the simulation and experimental steam generator.

• Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
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• 2003.05a
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• pp.225-230
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• 2003

Many port states such as New Zealand, the USA, Australia and Canada have strict regulations to prevent ships which arrive in their port from discharging polluted ballast water which contain harmful aquatic organisms and pathogens. They are notified that transfer of polluted ballast water can cause serious injury to public health and damage to property and environment. For this reason, they perceived that the ballast exchange in deep sea is the most effective method, together with submitting the ballast management plan which contains the effective exchange method, ballast system and safety consideration. In this study, we make an effort to develop optimum ballast water exchange management and in result of that, it provide more convenient and stable process for preparing ballast water management plan.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.8 no.3
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• pp.185-191
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• 2008

In this paper, experimental studies of a neural network (NN) control technique for non-model based position control of the x-y table robot are presented. Decentralized neural networks are used to control each axis of the x-y table robot separately. For an each neural network compensator, an inverse control technique is used. The neural network control technique called the reference compensation technique (RCT) is conceptually different from the existing neural controllers in that the NN controller compensates for uncertainties in the dynamical system by modifying desired trajectories. The back-propagation learning algorithm is developed in a real time DSP board for on-line learning. Practical real time position control experiments are conducted on the x-y table robot. Experimental results of using neural networks show more excellent position tracking than that of when PD controllers are used only.

• International Journal of Naval Architecture and Ocean Engineering
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• v.12 no.1
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• pp.314-324
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• 2020

Due to the nonlinearity and environmental uncertainties, the design of the ship's steering controller is a long-term challenge. The purpose of this study is to design an intelligent autopilot based on Extended Kalman Filter (EKF) trained Radial Basis Function Neural Network (RBFNN) control algorithm. The newly developed free running model scaled surface vessel was employed to execute the motion control experiments. After describing the design of the EKF trained RBFNN autopilot, the performances of the proposed control system were investigated by conducting experiments using the physical model on lake and simulations using the corresponding mathematical model. The results demonstrate that the developed control system is feasible to be used for the ship's motion control in the presences of environmental disturbances. Moreover, in comparison with the Back-Propagation (BP) neural networks and Proportional-Derivative (PD) based control methods, the EKF RBFNN based control method shows better performance regarding course keeping and trajectory tracking.