• Journal of Power System Engineering
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• v.4 no.4
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• pp.92-98
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• 2000

Modern manufacturing systems should cope with the frequent changes in a product model and disturbances in manufacturing process. The control system of such systems must cover a constant adaptation and high flexibility. Holonic Flexible Manufacturing Cell(HFMC) is introduced to handle these issues more successfully. It is based on the concept of autonomous co-operating agent, called 'Holon', which is a building block of a manufacturing system for transforming, transporting, storing and/or validating information and physical objects. In this paper the basic structure of the HFMC is represented by using Unified Modeling Language and Open architecture cell controller is developed for effective integration components of a manufacturing system. Also a new control model, called MuLOM(Multi-Layered Operation Model), is suggested to represent the control behaviour for a holonic flexible manufacturing cell control system.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.12 no.1
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• pp.70-76
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• 2013

Recently, the performance and function of electrical and electronic system in automotive vehicles is developing at a rapid rate with the advancement of IT technologies. Combined together with micro-controller and sensor technologies, the Vehicle Smart System (VSS) being developed to improve driver's convenience and comfort has been employed to a variety of applications. In addition to the convenience system, the Auto-parking Assistance System (AAS) that is now attracting a new attention has been already applied to some vehicles, but it is currently limited to luxury car models only. In this paper, we present a fuzzy controller that enables autonomous parking assistance without the AAS. The controller can perform the assistance with information provided from moving status, current position and steering angle as one is able to park a car based on his/her experience and knowledge for driving and parking. We have evaluated its performance of the proposed controller by simulation and tested the excellence of the controller by building a model vehicle embedded with the micro-controllers.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.21 no.47
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• pp.113-124
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• 1998

Manufacturing systems are becoming intelligent, decentralized, autonomous, which is so called as Intelligent Manufacturing Systems(IMS). In this paper, a method for efficient resource management in Holonic Manufacturing System which is one alternative of IMS, was developed. The developed method was evaluated with the current possible method and the results are shown.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.21 no.9
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• pp.92-97
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• 2022

In this paper, as a research on autonomous steering for agriculture, a sensor module for furrow recognition was developed through a low-cost distance sensor combination. The developed sensor module was applied to the vehicle, and when driving in a furrow curve, the autonomous steering success rate was 100% at a curvature of 20 m or more, and 70% at a curvature of 15 m or less. The self-steering success rate according to the ground condition showed a 100% success rate regardless of soil, weeds, or mulching film.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.20 no.4
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• pp.66-72
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• 2021

Since the behavior of an autonomous underwater vehicle (AUV) is influenced by disturbances and moments that are not accurately known, the depth control law of AUVs must have the ability to track the input signal and to reject disturbances simultaneously. Here, we proposed robust tracking control for controlling the depth of an AUV. An augmented closed-loop system is represented by an error dynamic equation, and we can easily show the asymptotic stability of the overall system by using a Lyapunov function. The robust tracking controller is consisted of the internal model of the command signal and a state feedback controller, and it has the ability to track the input signal and reject disturbances. The closed-loop control system is robust to parameter uncertainties. Simulation results showed the control performance of the robust tracking controller to be better than that of a P + PD controller.

• International Journal of Ocean System Engineering
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• v.1 no.1
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• pp.16-27
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• 2011

The depth and heading control of an autonomous underwater vehicle (AUV) are considered to follow the predetermined depth and heading angle. The proposed control algorithm was based on a sliding mode control, using estimated hydrodynamic coefficients. The hydrodynamic coefficients were estimated employing conventional nonlinear observer techniques, such as sliding mode observer and extended Kalman filter. Using the estimated coefficients, a sliding mode controller was constructed for a combined diving and steering maneuver. The simulated results of the proposed control system were compared with those of a control system that employed true coefficients. This paper demonstrated the proposed control system, and discusses the mechanisms that make the system stable and accurately follow the desired depth and heading angle in the presence of parameter uncertainty.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.17 no.2
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• pp.109-117
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• 2018

The experimental results are presented of an autonomous flight algorithm of a foldable quadcopter with airdrop launching functions. A foldable wing structure enabled the quadcopter to be inserted into a rocket container with limited space. The foldable quadcopter was then separated from the rocket in the air. The flight pattern was tracked using a global positioning system (GPS) with various sensors, including an inertial measurement unit (IMU) module until a designated target position was reached. Extensive field tests were conducted through an international rocket competition, ARLISS 2017, which was held in Black Rock Desert, Nevada, USA. The flight trajectory record of the experiments is stored in electrically erasable programmable read-only memory (EEPROM) embedded in the main control unit. The flight record confirmed that the quadcopter successfully separated from the rocket, executed flight toward the target for a certain length of time, and stably landed on the ground.

• Journal of the Korean Society for Precision Engineering
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• v.32 no.1
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• pp.39-47
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• 2015

Globalization, unpredictable markets, increased products customization and frequent changes in products, production technologies and machining systems have become a complexity in today's manufacturing environment. One key strategy for coping with the evolution of this situation is to develop or apply an enable technology such as intelligent manufacturing. Intelligent manufacturing system (IMS) is characterized by decentralized, distributed, networked compositions of heterogeneous and autonomous systems. The model of IMS is inherited from the organization of the living systems in biology and nature so that the manufacturing system has the advanced characteristics inspired from biology such as self-adaptation, self-diagnosis, and selfhealing. To prove this concept, an innovative system with applying the advanced information and communication technology such as internet of things, cognitive agent are proposed to integrate, organize and allocate the machining resources. Innovative system is essential for modern machining system to flexibly and quickly adapt to new challenges of manufacturing environment.

• Journal of Mechanical Science and Technology
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• v.15 no.5
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• pp.544-554
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• 2001

A shop floor can be considered as an important level to develop Computer Integrated Manufacturing system (CIMs). However, a shop floor is a dynamic environment where unexpected events continuously occur, and impose changes to the planned activities. To deal with this problem, a shop floor should adopt an appropriate control system that is responsible for the coordination and control of the manufacturing physical flow and information flow. In this paper, a hybrid control system is described with a shop floor activity methodology called Multi-Layered Task Initiation Diagram (MTD). The architecture of the control model contains three levels: i.e., he shop floor controller (SFC), the intelligent agent controller (IAC) and the equipment controller (EC). The methodology behind the development of the control system is an intelligent multi-agent paradigm that enables the shop floor control system to be an independent, an autonomous, and distributed system, and to achieve an adaptability to change of the manufacturing environment.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.20 no.9
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• pp.70-75
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• 2021

We developed a platform that was capable of autonomous steering in a furrow environment. It was developed to autonomously control steering by recognizing the furrow using a laser distance, three-axis tilt, and temperature sensor. The performance evaluation indicated that the autonomous steering success rate was 99.17%, and it was possible to climb up to 5° on the slope. The usage time was approximately 40 h, and the maximum speed was 6.7 km/h.