• Journal of the Korean Society for Precision Engineering
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• v.15 no.12
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• pp.55-61
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• 1998

Recently, the needs of machining technologies of very small parts have been increasing with advent of micro-revolution. These technologies have mostly used the method applied to semi-conductor production process such as LIGA, etc. But they have serious difficulties to settle down in terms of workpiece materials, machining thickness, 3-dimensional structure. Therefore. mciro-machining technology using EDM(Electrical Discharge Machining) was proposed. It is very difficult to machine the micro-parts (microshaft, microhole) using conventional machining. Micro-machining using BDM can machine the micro-parts easily because it requires little machining force. This MEDM(Micro-EDM) need the capabilities to move a electrode and control a discharge energy precisely, and the gap control strategy to maintain the optimal discharge condition is necessary. Therefore, in this study, the new EDM machine with high precision motion stage and high-performance EDM device was developed. Using this MEDM machine, we have machined microshaft and microhole with various shapes and sizes.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2004.10a
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• pp.1327-1330
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• 2004

An underwater robotic system has been developed and applied to visual inspection of reactor vessel internals. The Korea Electric Power Robot for Visual Test (KeproVt) consists of an underwater robot, a vision processor-based measuring unit, a master control station and a servo control station. The robot guided by the control station with the measuring unit can be controlled to have any motion at any position in the reactor vessel with $\pm$1 cm positioning and $\pm$2 degrees heading accuracies with enough precision to inspect reactor internals. A simple and fast installation process is emphasized in the developed system. The developed robotic system was successfully deployed at the Younggwang Nuclear Unit 1 for the visual inspection of reactor internals.

• International Journal of Precision Engineering and Manufacturing
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• v.6 no.1
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• pp.31-35
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• 2005

Higher productivity requires high-speed motion of machine tool axes. The iron core linear DC motor (LDM) is widely accepted as a viable candidate for high-speed machine tool feed unit. LDM, however, has two inherent disturbance force components, namely cogging and thrust force ripple. These disturbance forces directly affect the tracking accuracy of the feeding system and must be eliminated or reduced. In order to reduce motor ripple, this research adapted the feedforward compensation method and neural network control. Experiments carried out with the linear motor test setup show that these control methods are effective in reducing motor ripple.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1997.04a
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• pp.125-130
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• 1997

In this paper, it is 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 TMS320C3x 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, andsuitable for implementation of robust control.

• Journal of the Korean Society for Precision Engineering
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• v.19 no.12
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• pp.45-56
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• 2002

A pneumatic servo system requiring a fine gap control in a photo-electric sensor which is used for a LCD array detection device is introduced. The gap controlled by the pneumatic servo system remains within around 50~80 ${\mu}{\textrm}{m}$, and the system possesses an effect to eliminate undesirable particles on the LCD plate by blowing air out. The air flow rate is initially controlled by a servo valve and expanded by a booster valve, thus the controlled air pressure contributes to maintaining an appropriate gap between the LCD plate and photo-electric sensor An air floating plate of two degrees of freedom is designed and fabricated, and a fine tilting motion control is also implemented by assigning different gap commands. The pressure control and direct gap control are proposed, and each performance is verified experimentally.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1999.10a
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• pp.113-118
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• 1999

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 n 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 Precision Engineering Conference
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• 1996.11a
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• pp.396-400
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• 1996

It is prerequisite to apply dynamics controller to control robot manipulator required to perform fast and Precise motion. In this Paper, we Propose an adaptive 3earning control method for the dynamic control of a robot manipulator. The proposed control scheme is made up of PD controller in the feedback loop and the adaptive learning controller in the feedforward loop. This control scheme has the ability to estimate uncertain dynamic parameters included intrinsically in the system and to achieve the desired performance without the nasty matrix operation. The proposed method is applied to a SCARA robot and experimentally verified.

• Journal of the Korean Society for Precision Engineering
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• v.15 no.10
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• pp.165-171
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• 1998

An axial electromagnetic levitation system using attractive force is a highly nonlinear system due to the nonlinearity of materials, variable air gap and flux density. To control the levitating system with large air gap, a conventional PID control based on the linear model is not satisfactory to obtain the desired performance and the position tracking control of the sinusoidal motion by simulation results. Thus, sliding mode control(SMC) based on the input-output linearization is suggested and evaluated by simulation and experimental approaches. Usefulness of the SMC to this system is conformed experimentally. If the expected variation of added mass can be included in the gain conditions and the model, the position control performance of the electromagnetic levitation system with large air gap will be improved with robustness.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.69.2-69
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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.

• International Journal of Precision Engineering and Manufacturing
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• v.7 no.1
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• pp.35-41
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• 2006

In this paper, we develop anti-sway control in proposed techniques for an ATC system. The developed algorithm is to build the optimal path of container motion and to calculate an anti-collision path for collision avoidance in its movement to the finial coordinate. Moreover, in order to show the effectiveness in this research, we compared NNP PID controller to be tuning parameters of controller using NN with 2-DOF PID controller. The experimental results jar an ATC simulator show that the proposed control scheme guarantees performances, trolley position, sway angle, and settling time in NNP PID controller than other controller. As a result, the application of NNP PID controller is analyzed to have robustness about disturbance which is wind of fixed pattern in the yard.