• Transactions of the Korean Society of Machine Tool Engineers
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• v.13 no.4
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• pp.87-94
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• 2004

Recently, technical trend in machine tools is focused on enhancing of speed, accuracy and reliability. The high speed usually results in thermal displacement and structural deformation. To minimize the thermal effect, precision machine tools adopt a high precision cooling system. This study proposes a temperature control for an oil cooler system using Pill control with fuzzy logic. In the cooler system, refrigerant flow rate is controlled by rotational speed of a compressor, and outlet oil temperature is selected as the control variable. The fuzzy control rules iteratively correct PID parameters to minimize the error and difference between the outlet temperature and the reference temperature. Here, ambient temperature is used as the reference one. To show the effectiveness of the proposed method, a series of experiments are conducted for an oil cooler system of machine tools, and the results are compared with the ones of a conventional Pill control. The experimental results show that the proposed method has advantages of faster response and smaller overshoot.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.10a
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• pp.577-580
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• 1995

This paper suggests direct-acting hydraulic circuit to control clutches and brakes in automatic transmission. As only one pressure control valve controls the pressure of several friction elements with accumulators in conventional hydraulic circuit, the controllable range is limited. In addition, it is difficult to control the fine timing between apply clutch and release clutch. So, we designed new method to control the pressure of clutch which uses ressure control valve and pressure control solenoid valve independently in each friction element. through this structure improvement of hydraulic circuit, we can control the pressure of clutches and brakes finely and fine timing of between apply clutch and release clutch.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.9
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• pp.840-846
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• 2004

In this study, the performance of a heavy load pointing system has been investigated. The PI controller are being widely used in industrial application because of simple, cheap, and excellent performance. However, the requirement for control precision becomes higher and higher, as well as the plants becomes more and more complex. In order to achieve the satisfied control performance, we have to consider the affection of nonlinear factor contained in plant. In this paper, the neural-PI control law have been evaluated. The proposed controller is compared with the existing controllers through simulations, and the results show that the pointing accuracy of the proposed control system is improved against the disturbance induced by vehicle running on the bump course.

• Proceedings of the KIEE Conference
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• 1992.07a
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• pp.422-424
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• 1992

In this paper, we are designed a hierachical system controller and builed a robot system for high precision assembly consisting in multi-arms and multi-sensor. For the control of a multi-arms robot system, the robot system are consisted of cell controller, station controller and device. The Operating System of a cell controller is VxWorks for real-time multi-processing. Using by C-language, we are proposed a multi-arms robot control language based a RCCL, and this control language is partially implemented and tested in multi-robot control system.

• 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 Precision Engineering Conference
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• 1997.10a
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• pp.462-466
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• 1997

Proportional directional control valves (PDCVl adjust the amount of flow as well as flow direction in response to an electrical signal. This valves includes direct operated valves with or without spool position feedback. This paper investigates if it is possible to control pressure of fluids by means of the PDCV. A pressure signal is feed back to the Proportional-Integral (PI) controller, which is based upon a personal computer (PC). The PI control algorithm is implemented in a graphical programming language of LabVIEW. The results of experiments show the PDCV can be used a multi function valve of pressure control as well as direction control.

• International Journal of Precision Engineering and Manufacturing
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• v.3 no.3
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• pp.12-20
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• 2002

As numerous sensors and actuators are used in many automated systems, various industrial networks are adopted for real-time distributed control. In order to take advantages of the networking, however, the network implementation should be carefully designed to satisfy real-time requirements considering network induced delays. This paper presents an implementation scheme of a networked control system via Profibus-DP network fur real-time distributed control. More specifically, the effect of the network induced delay on the control performance is evaluated on a Profibus-DP testbed. Also, two conventional PID gain tuning methods are slightly modified fur fouling controllers fur the networked control system. With appropriate choices for gains, it is shown that the networked control system can perform almost as well as the traditional control system.

• Journal of the Korean Society for Precision Engineering
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• v.5 no.2
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• pp.43-55
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• 1988

The control system of a drum boiler is very complex since the evaporization process in the boiler is a multivariable system which is affected one another. This study is concerned with the dynamic characteristics of the boiler process and improving methods of performance of a drum boiler control system. The PID control with feedforward of disturbances and the optimal regulator are compared, and the effects of control parameters on the performance of a boiler control system are investigated. From simulation, it is found that profer adjustment of control parameters significant improvement of response and that performance of a optimal regulated control system is better than that of a conventional PID control system.

• 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 for Precision Engineering
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• v.27 no.3
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• pp.118-126
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• 2010

The automated mechanical transmission(AMT) is composed of electronic control management(ECM) and automatic shift gear(ASG). The AMT has advantages which are high efficiency of manual transmissions(MT) and offer operation convenience similar to automatic transmissions(AT). However, it has defects that are the torque gap during gear shift transients and shift time is long. To reduce such defects, it is necessary practically to evaluate error and characteristics as developing simulation model before the control algorithm is applied. In this paper, models are composed of vehicle model and AMT shift control model. Particularly AMT shift control model consists of main clutch management model (MCM) and shift control management model(SCM). The developed models were verified by comparing the simulated and experimental results under the same operational conditions. It can also be used to evaluate shift algorithm.