• Journal of the Korea Institute of Building Construction
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• v.20 no.6
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• pp.555-566
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• 2020

Recently, the aging of public facilities in Korea have accelerated, and the existing framework for facility management is shifting toward to facility asset management in terms of performance-based proactive control. Therefore, the operation of public facility involves both safety assurance from the deteriorated facilities and management capabilities for sustainable maintenance in the required valuation and level of service, such as valuation of facility assets, life-cycle management plans, financing, and so on. In this study, the Facility Asset Management Indicator(FAMI) has been developed for public facility asset management, and it provides the quantitative management grade, based on international standards, such as ISO 55000 series and International Infrastructure Management Manual(IIMM). The FMMI includes 10 key areas to apply a diagnosis model into management capabilities, 113 detailed elements, and 5 maturity grades. As the importance of public facility asset management is increasing constantly, this is expected to identify previously the strengths and weaknesses of public facility operating institutions. Eventually, they can obtain the effective ways to improve their own capabilities, minimize the public funds, establish the strategies for innovating the current management structures, and operate stably the facilities in the required performance.

• 제어로봇시스템학회:학술대회논문집
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• 1990.10a
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• pp.36-40
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• 1990

Conventional back propagation learning is generally characterized by slow and rather inaccurate learning which makes it difficult to use in control applications. A new multilayer perception architecture and its learning algorithm is proposed that consists of a Kohonen front layer followed by a back propagation network. The Kohonen layer selects a subset of the hidden layer neurons for local tuning. This architecture has been tested on the inverse kinematic solution of robot manipulator while demonstrating its fast and accurate learning capabilities.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.377-377
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• 2000

Current software cost estimation models, such as the 1951 COCOMO, its 1987 Ada COCOMO update, is composed of nonlinear models, such as product attributes, computer attributes, personnel attributes, project attributes, effort-multiplier cost drivers, and have been experiencing increasing difficulties in estimating the costs of software developed to new lift cycle processes and capabilities. The COCOMO II is developed fur new forms against the current software cost estimation models. This paper provides a case-based analysis result of the cost driver in the software cost models, such as COCOMO and COCOMO 2.0 by fuzzy and neural network.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.1346-1349
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• 1993

In this paper, we describe the use of certain optimization techniques, principally dynamic programming and high level computational methods, to enhance the capabilities of a fuzzy adaptive neural network controller which we had developed for on-line control and adaption on complex nonlinear processes. Potential applications to an array of processes from diverse fields are discussed.

• Journal of the Korea Institute of Military Science and Technology
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• v.15 no.4
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• pp.366-373
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• 2012

In this paper, serious changes in the electromagnetic environment with increasing power and energy capabilities for electric driving and military mission are discussed. Design and control strategies on the Electro-Magnetic Compatibility(EMC) for the series hybrid electric vehicle are proposed to minimize the effects of electromagnetic interferences.

• Journal of Mechanical Science and Technology
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• v.14 no.8
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• pp.836-844
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• 2000

In this research any abnormal motion of a vehicle is detected by utilizing the difference between the reference and actual yaw velocities as sell as the information on vehicle slip angle and slip angular velocity. This information is then used as a criterion for execution of the yaw moment control. A yaw moment control algorithm based on the brake control is proposed for improving the directional stability of the vehicle. The controller executes brake controls to provide each wheel with adequate brake pressures, which generate the needed yaw moment. It is shown that the proposed yaw moment control logic can provide excellent cornering capabilities even on low friction roads. This active control scheme can prevent a vehicle from behaving abnormally, and can assist normal drivers in coping with dangerous situations as well as experienced drivers.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.10
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• pp.1523-1531
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• 2017

In general, the thrust vector control should be fast and stable in the initial launch phase. Two types of conventional controllers, one is for pitch angle control and the other is for pitch rate control, are designed based on the equation of motion without aerodynamics and are compared in the viewpoints of the stability margin and the time response performance. Also analyzed are the rejection capabilities to cope with high aerodynamic disturbances caused by high angle of attacks in initial booting phase. Additionally, time response features at actuator saturation are investigated. Based on those results, we suggest a controller structure which is more suitable for thrust vector control of missiles at initial booting phase.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2001.04a
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• pp.255-260
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• 2001

This paper presents a new approach to the design of neural control system using digital signal processors in order to improve the precision and robustness. Robotic manipulators have become increasingly important in the field of flexible automation. High speed and high-precision trajectory tracking are indispensable capabilities for their versatile application. The need to meet demanding control requirement in increasingly complex dynamical control systems under significant uncertainties, leads toward design of intelligent manipulation robots. The TMS320C31 is used in implementing real time neural control to provide an enhanced motion control for robotic manipulators. In this control scheme, the networks introduced are neural nets with dynamic neurons, whose dynamics are distributed over all the network nodes. The nets are trained by the distributed dynamic back propagation algorithm. The proposed neural network control scheme is simple in structure, fast in computation, and suitable for implementation of real-time control. Performance of the neural controller is illustrated by simulation and experimental results for a SCARA robot.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1996.10a
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• pp.133-137
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• 1996

This paper presents a new approach to the design of neural control system using digital signal processors in order to improve the precision and robustness. Robotic manipulators have bevome increasingly important in the field of flexible automation. High speed and high-precision trajectory tracking arre indispensable capabilities for their versatile application. the need to meet demanding control requirement in increasingly complex dynamical control systems under sygnificant uncertainties leads toward design of implementing real time neural control to provide an enhanced motion control for robotic manipulators. In this control scheme the ntworks intrduced are neural nets with dynamic neurouns whose dynamics are distributed over all the network nodes. The nets are trained by the distributed dynamic are distributed over all the network nodes. The nets are trained by the distributed dynamic back propagation algorithm. The proposed neural network control scheme is simple in structure fast in computation and suitable for implementation of real-time control, Performance of the neural controller is illustrated by simulation and experimental results for a SCAEA robot.

• Journal of the Korean Society of Industry Convergence
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• v.16 no.4
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• pp.127-132
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• 2013

We describe a research about remote control of mobile robot based on voice command in this paper. Through real-time remote control and wireless network capabilities of an unmanned remote-control experiments and Home Security / exercise with an unmanned robot, remote control and voice recognition and voice transmission are possible to transmit on a PC using a microphone to control a robot to pinpoint of the source. Speech recognition can be controlled robot by using a remote control. In this research, speech recognition speed and direction of self-driving robot were controlled by a wireless remote control in order to verify the performance of mobile robot with two drives.