• The Transactions of the Korea Information Processing Society
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• v.6 no.9
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• pp.2365-2372
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• 1999

The reusability measurement model should satisfy the following conditions : 1) can insert and delete metrics and components easily, 2) can compare and evaluate components quantitatively on the basis of validation, 3) don't require certain preassumed knowledge, and 4) can compute significance of each measurement attribute objectively. Therefore, in this paper, we propose a new reusability measurement model that can satisfy the above requirements. Our model selects the appropriate measurement attributes and calculates the relative significance of them by using rough set. Then, in order to measure the reusability of component, it integrates the significance of attributes and the measured value of them by using fuzzy integral. Finally, we apply our model to the reusability measurement of the function-oriented components and validate our model through statistical technique.

• Journal of the Korean Society of Safety
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• v.8 no.4
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• pp.91-94
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• 1993

The main purpose of this study was to develop fuzzy models in order to decide system failure rate in industrial accident prevention. The purposed linguistic approach uses the Zadeh's concept of a linguistic variable with value which are not number. The problem of measurement Is the assignment of numbers to reprresnt properties of the involved events, object, or situation. Thus, in this study, part standard compatibility function was used.

• Journal of Electrical Engineering and Technology
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• v.12 no.6
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• pp.2268-2277
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• 2017

As constantly increasing wind power penetrates power grid, wind power plants (WPPs) are exerting a direct influence on the traditional power system. Most of WPPs are using variable speed constant frequency (VSCF) wind turbines equipped with doubly fed induction generators (DFIGs) due to their high efficiency over other wind turbine generators (WTGs). Therefore, the analysis of DFIG has attracted considerable attention. Precisely measuring optimum reference speed is basis of utilized maximum wind power in electric power generation. If the measurement of wind speed can be easily taken, the reference of rotation speed can be easily calculated by known system's parameters. However, considering the varying wind speed at different locations of blade, the turbulence and tower shadow also increase the difficulty of its measurement. The aim of this study is to design fuzzy controllers to replace the wind speedometer to track the optimum generator speed based on the errors of generator output power and rotation speed in varying wind speed. Besides, this paper proposes the fuzzy adaptive PID control to replace traditional PID control under rated wind speed in variable-pitch wind turbine, which can detect and analyze important aspects, such as unforeseeable conditions, parameters delay and interference in the control process, and conducts online optimal adjustment of PID parameters to fulfill the requirement of variable pitch control system.

• The Journal of the Korea Contents Association
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• v.12 no.2
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• pp.1-9
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• 2012

This paper presents an algorithm for depression diagnosis using the Neural Network with Weighted Fuzzy Membership functions (NEWFM) and heart rate variability (HRV). In the algorithm, 22 different features were initially extracted from the HRV signal by frequency domain, time domain, wavelet transformed, and Poincar$\acute{e}$ transformed feature extraction methods; of these 6 optimal features were selected by significance evaluation using Non-overlap Area Distribution Measurement (NADM) based on NEWFM. The proposed algorithm uses these 6 optimal features to diagnose depression with an accuracy of 95.83%.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.1
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• pp.104-111
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• 2000

A fuzzy logic Run-by-Run(RbR) controller and an in -line wafer characteristics prediction scheme for the rapid thermal processing system have been developed for the study of process repeatability. The fuzzy logic RbR controller provides a framework for controlling a process which is subject to disturbances such as shifts and drifts as a normal part of its operation. The fuzzy logic RbR controller combines the advantages of both fuzzy logic and feedback control. It has two components : fuzzy logic diagnostic system and model modification system. At first, a neural network model is constructed with the I/O data collected during the designed experiments. The wafer state after each run is assessed by the fuzzy logic diagnostic system with featuring step. The model modification system updates the existing neural network process model in case of process shift or drift, and then select a new recipe based on the updated model using genetic algorithm. After this procedure, wafer characteristics are predicted from the in-line wafer characteristics prediction model with principal component analysis. The fuzzy logic RbR controller has been applied to the control of Titanium SALICIDE process. After completing all of the above, it follows that: 1) the fuzzy logic RbR controller can compensate the process draft, and 2) the in-line wafer characteristics prediction scheme can reduce the measurement cost and time.

• Journal of Information Processing Systems
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• v.7 no.4
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• pp.595-612
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• 2011

Most organizations use performance appraisal system to evaluate the effectiveness and efficiency of their employees. In evaluating staff performance, performance appraisal usually involves awarding numerical values or linguistic labels to employees performance. These values and labels are used to represent each staff achievement by reasoning incorporated in the arithmetical or statistical methods. However, the staff performance appraisal may involve judgments which are based on imprecise data especially when a person (the superior) tries to interpret another person's (his/her subordinate) performance. Thus, the scores awarded by the appraiser are only approximations. From fuzzy logic perspective, the performance of the appraisee involves the measurement of his/her ability, competence and skills, which are actually fuzzy concepts that can be captured in fuzzy terms. Accordingly, fuzzy approach can be used to handle these imprecision and uncertainty information. Therefore, the performance appraisal system can be examined using Fuzzy Logic Approach, which is carried out in the study. The study utilized a Cascaded fuzzy inference system to generate the performance qualities of some University non-teaching staff that are based on specific performance appraisal criteria.

• Journal of the Korean Society of Safety
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• v.26 no.4
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• pp.69-79
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• 2011

This paper proposes a GA-based optimal fuzzy control technique for the vibration control of earthquakeexcited adjacent structures interconnected with semi-active magneto-rheological(MR) dampers. Rule-based fuzzy logic controllers are designed first by implementing heuristic knowledge and the genetic algorithm(GA) is then introduced to optimally tune the fuzzy controllers for enhancing the seismic performance of semi-active control system. For practical implementation, the fuzzy controller simply uses locally measured responses of the dampers involved and directly returns the input voltage to the magneto-rheological dampers in real time through the fuzzy inference mechanism. The local measurement based fuzzy controller provides optimal damping force in a decentralized manner so that it does not require a primary central controller unlike the conventional semi-active control techniques. As a result, it can avoid the unbridgeable discrepancy between the desired control force and the actual damper force that may occur in the conventional control approaches. The validity and effectiveness of the proposed control method are shown numerically on two 20-story earthquake-excited buildings interconnected with MR dampers.

• Journal of the Semiconductor & Display Technology
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• v.6 no.4
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• pp.17-22
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• 2007

Vibration isolation equipments are mostly required in precise measurement and manufacturing system. Among all the vibration isolation equipments, air-spring is the most widely used equipment because of low resonant frequency and high damping ratio. In this study, we used Takagi-Sugeno fuzzy method to design an active vibration isolation system using air-spring, and compared the fuzzy method with passive control method and PID control method. Due to the non-linearity characteristics of air-spring, fuzzy controller was verified to be the most effective both in simulation and experiment.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.28B no.7
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• pp.557-565
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• 1991

The activated sludge process is a commonly used method for terating sewage and waste waters. The process is chatacterized by a lack of measurement instrumentations and control goals that are not always clear and not well understood. In such process, fuzzy control concept may be able to be adapted, do this paper presents a design method for fuzzy controller based on a selected sub-rule set from the total rule set and a multivariable fuzzy reasoning algorithms. In order to achievesystematic and efficient control of the activated sludge process under a great deal of disiutbances and a variety of perfotmance characteristics, a top-level rule-based fuzzy controller os proposed which provises lower-controllers with the suitable set-points according tothe onput-output states of the process.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.129.5-129
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• 2001

When a robot manipulator performs some task like grinding or assembling, not only the position control but also the force control of the tools connected to the robot must be controlled. But at this time We were received the uncertainty problems of system information for the force control, for example disturbance, senor resolution and measurement noise. Therefore we proposed fuzzy logic control method instead of existing control theory for the robot manipulator control, for example PID control method. In this paper, We proposed hybrid position/force control of robot manipulator using fuzzy logic control method. To show the validity of the proposed fuzzy controller, We compared fuzzy controller with conventional PID controller.