• Journal of the Korea Academia-Industrial cooperation Society
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• v.3 no.1
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• pp.1-4
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• 2002

A short shot is a molded part that is incomplete because insufficient material was injected into the mold. Any factors that increase the resistance of polymer melt to flow or prohibit delivery of sufficient material into the cavity can cause a short shot. Inappropriate injection pressure is one of the most common factors which cause a short shot. Conventionally, domain experts in injection molding decide and modify the pressure based on their experience. It is difficult for a non-expert to decide the pressure properly with the considerations such as a part dimension, shape, and other processing variables. In this study, fuzzy algorithm is proposed to standardize the empirical determination of the pressure so that not only the experts but also non-experts can find the appropriate injection pressure easily. To acquire the more accurate results. domain experts should be interviewed and then technical documents which are collected from the experts should be restored in the fuzzy rule base. But in this study, simulations have been done by using C-MOLD to settle the rule base because it takes much time and also it's difficult to meet and interview the experts.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1993.10a
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• pp.142-148
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• 1993

Recectly, development of expert system utilizing the domain specific knowledge focuses upon the machining operations. This paper describes an expert system for selecting the optimum grinding wheel based on the Analytic Hierarchy Process and Fuzzy Logic. Knowledge-base, in this system, for selecting of grinding wheel is designed to appling the knowhow and experience knowledge of skilled hands. In this paper, firstly determination method of fuzzy membership function utilizing the qualitative knowledge, and then selection of the optimum wheel from among the available components according to Saaty's priority rule are described. Lastly,some implementation results are suggested.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.404-407
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• 1993

In this paper, a new PID fuzzy controller(FC) is presented. The linguistic control rules of PID FC is separated into two parts : one is e-.DELTA.e part, and the other is .DELTA.$^{2}$e - .DELTA.e part. And then two FCs employing these rule base individually are synthesized. The control input to the process is decided by taking weighted mean of the outputs of two FCs. The proposed PID FC improve the transient response of the system and gives better performance than the conventional PI FC.

• Journal of Industrial Technology
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• v.13
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• pp.43-48
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• 1993

In this paper, a new PID fuzzy controller (FC) is presented. The linguistic control rules of PID FC is separated into two parts : one is $e-{\Delta}e$ part, and the other is ${\Delta}^2e-{\Delta}e$ part. And then two FCs employing these rule base indivisually are synthesized. The control input to the process is decided by taking weighted mean of the outputs of two FCs. The proposed PID FC improve the transient response of the system and gives better performance than the conventional PI FC.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.761-764
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• 1993

In this paper we consider techniques for reducing the generated number of rules in learning fuzzy controllers of the state-space action-reinforcement type that can be simply implemented and that behave well in the presence of process noise. Fewer rules lead to better performance, less contradiction in controller action estimation, smaller required execution-time and make it easier for a human to comprehend the generated rules and possibly intervene.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.268-271
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• 1998

this paper presents the potential application of fuzzy logic to the automatic incident detection system. While the conventional incident detection algorithms are based on a binary decision process, the algorithm using fuzzy logic can incorporate ambiguity which occurs in determining incidents. Since collecting good amount of data to construct data base for incidents is pretty expensive, a traffic simulator called FRESIM is used to simulate traffic condition in a freeway. Incident data are obtained by changing input parameters of the simulator and the fuzzy algorithm generates fuzzy rule for determining normal and incident traffic conditions. In this paper, various steps are described to test the algorithm and its results are summarized.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.10a
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• pp.342-345
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• 1995

This paper describes the design process and the experimental results of a fuzzy logic controller to control the tip position of a fixible-link manipulator, directly driven by a AC motor, with a large payload. The joint angle fuzzy logic controller is designed without a costly nonlinear system analysis of the flexible manipulator and the AC motor drive system. The state variables for the fuzzy logic controller are joint angle, joint velocity, link deflection, and link deflection velocity. The simulation and experimental results show that the joint position control is not satisfactory when the controller is designed under the assumption of no link flexibility and that stable joint position control and link vibration suppression can be cahieved with the fuzzy logic controller suggested in this paper.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.5 no.7
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• pp.1374-1383
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• 2001

In the fuzzy control method behaves more robustness than conventional control method, we propose a intelligent control method that membership functions and scaling factor of the fuzzy logic controller are optimized by genetic algorithm under off-line, and then fuzzy logic controller is constructed by the optimization parameters under on-line. In order to verify the usefulness of the proposed control method, we are applied to one link manipulator, and confirmed that the proposed control method is reduced the fuzzy rule base and is the better performance than the conventional fuzzy control method.

• Journal of the Korean Institute of Intelligent Systems
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• v.5 no.3
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• pp.52-63
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• 1995

A neuro-fuzzy algorithm is presented for nuclear reactor power control in a pressurized water reactor. Automatic reacotr power control is complicated by the use of control rods because of highly nonlinear dynamics in the axial power shape. Thus, manual shaped controls are usually employed even for the limited capability during the power maneuvers. In an attempt to achieve automatic shape control, a neuro-fuzzy approach is considered because fuzzy algorithms are good at various aspects of operator's knowledge representation while neural networks are efficinet structures capable of learning from experience and adaptation to a changing nuclear core state. In the proposed neuro-fuzzy control scheme, the rule base is formulated based ona multi-input multi-output system and the dynamic back-propagation is used for learning. The neuro-fuzzy powere control algorithm has been tested using simulation fesponses of a Korean standard pressurized water reactor. The results illustrate that the proposed control algorithm would be a parctical strategy for automatic nuclear reactor power control.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.105.5-105
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• 2001

This paper describes a fuzzy steering controller for an autonomous mobile robot with MR sensor. Using the magnetic field(Bx, By, Bz) obtained from the MR sensor, we designed fuzzy controller for driving on the road center. Fuzzy rule base was built to magnetic field(Bx, By, Bz). To develop an autonomous mobile robot simulation program, we have done modeling MR sensor, dynamic model of mobile robot and coordinate transformation. A computer simulation of the robot including mobile robot dynamics and steering was used to verify the steering performance of the mobile robot controller using the fuzzy logic Good results were obtained by computer simulation. So, we confirmed the robustness of the proposed fuzzy controller by computer ...