• International Journal of Fuzzy Logic and Intelligent Systems
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• v.9 no.1
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• pp.36-41
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• 2009

Self organizing map(SOM) is one of the unsupervised methods based on the competitive learning. Many clustering works have been performed using SOM. It has offered the data visualization according to its result. The visualized result has been used for decision process of descriptive data mining as exploratory data analysis. In this paper we propose improvement of SOM using stratified sampling of statistics. The stratification leads to improve the performance of SOM. To verify improvement of our study, we make comparative experiments using the data sets form UCI machine learning repository and simulation data.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.15 no.4
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• pp.300-304
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• 2015

A low bit rate speech coder based on the non-uniform sampling technique is proposed. The non-uniform sampling technique is based on the detection of inflection points (IP). A speech block is processed by the IP detector, and the detected IP pattern is compared with entries of the IP database. The address of the closest member of the database is transmitted with the energy of the speech block. In the receiver, the decoder reconstructs the speech block using the received address and the energy information of the block. As results, the coder shows fixed data rate contrary to the existing speech coders based on the non-uniform sampling. Through computer simulation, the usefulness of the proposed technique is shown. The SNR performance of the proposed method is approximately 5.27 dB with the data rate of 1.5 kbps.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.16 no.4
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• pp.276-280
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• 2016

A fixed rate speech coder based on the filter bank and the non-uniform sampling technique is proposed. The non-uniform sampling is achieved by the detection of inflection points (IPs). A speech block is band passed by the filter bank, and the subband signals are processed by the IP detector, and the detected IP patterns are compared with entries of the IP database. For each subband signal, the address of the closest member of the database and the energy of the IP pattern are transmitted through channel. In the receiver, the decoder recovers the subband signals using the received addresses and the energy information, and reconstructs the speech via the filter bank summation. As results, the coder shows fixed data rate contrary to the existing speech coders based on the non-uniform sampling. Through computer simulation, the usefulness of the proposed technique is confirmed. The signal-to-noise ratio (SNR) performance of the proposed method is comparable to that of the uniform sampled pulse code modulation (PCM) below 20 kbps data rate.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.12
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• pp.1479-1485
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• 1999

This paper proposes a fuzzy decision making method for power transformer protection to identify an internal fault from other transient states such as inrush, over-excitation and an external fault with current transformer (CT) saturation. In this paper, analyzing over 300 EMTP simulations of disturbances, four input variables are selected and fuzzified. At every sampling interval from half to one cycle after a disturbance, from the EMPT simulations, different fuzzy rule base is composed of twelve if-then fuzzy rules associated with their basic probability assignments for singleton- or compound-support hypotheses. Dempster's rule of combination is used to process the fuzzy rules and get the final decision. A series of test results clearly indicate that the method can identify not only an internal fault but also the other transients. The average of relay operation times is about 12(ms). The proposed method is implemented into a Digital Signal Processor (TMS320C31) and tested.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.22 no.3
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• pp.644-653
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• 1998

In resistance spot weld, the assurance of weld quality has been a long-standing problem. Since the weld nuggets if resustance spot welding form between the workpieces, visual detection of defects in usually impossible. Welding quality of resistance spot welding can be verified by non destructive and destructive inspections such as X-Ray inspection and testing of weld strength. But these tests, in addition to being time-consuming and costly, can entail risks due to sampling basis. The purpose of this study is the development of the monitoring system based on fuzzy inference, aimed at diagonosis of quality in resistance spot welding. The fuzzy inference system consists of fuzzy input variables, fuzzy membership functions and fuzzy rules. For inferring the welding quality(strength), the experimental data of the spot welding were acquired in various welding conditions with the monitoring system designed. Some fuzzy input variables-maximum, slop and difference values of electrode movement signals-were extracted from the experimental data. It was confirmed that the fuzzy inference values of strength have a .${\pm}$5% error in comparison with actual values for the selected welding conditions(9-10.5KA, 10-14 cycle, 250-300 $kg_f$). This monitoring system can be useful in improving the quality assurance and reliability of the resistance spot welding process.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10b
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• pp.265-271
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• 1992

It is the purpose of this paper to present a dialogical designing method for control system using a rough grasp of the unknown process property. We deal with a single-input single-output feedback control system with a fuzzy controller. The process property is roughly estimated by the step response, and the fuzzy controller is interactively modified according to the operator's requests. The modifying rules mainly derived from computer simulation are useful for almost every process, such as an unstable process and a non-minimum phase process. The fuzzy controller is tuned by taking notice of four characteristics of the step response: (1) rising time, (2) overshoot, (3) amplitude and (4) period of vibration. The tuning position of the controller is fourfold: (1) antecedent gain factor GE or GCE, (2) consequent gain factor GDU, (3) arrangement of the antecedent fuzzy labels and (4) arrangement of the control rules. The rules give an instance to the respective items of the controller in an effective order. The modified fuzzy PI controller realizes a good response of a stable process. However, because the GDU tuning becomes difficult for the unstable process, it is necessary to evaluate the stability of the process from the initial step response. The fuzzy PI controller is applied to the process whose initial step response converges with GDU tuning. The fuzzy PI controller with modified sampling time is applied to the process whose step response converges under the repeated application of the GDU tuning. The fuzzy PD controller is applied to the process whose step response never converges by the GDU tuning.

• Proceedings of the KIEE Conference
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• 2002.07b
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• pp.1084-1087
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• 2002

This paper presents an improved fuzzy logic-based adaptive PWM technique. A fuzzy logic- based adaptive PWM technique determines the optimal output voltage vector which takes into account both direction of back-emf and direction of current error vector. This technique has a simple structure and a good level of stability, but it has disadvantages. The longer sampling period, the larger current error. Because there is no considerations of the current error magnitude of each phases. The proposed method improves the control performance by selecting the optimum switching pattern in which the magnitudes of current errors are considered introducing space vector concept. Simulation results using Matlab/Simulink show that the proposed control method reduces current error keeping the merit of previous one.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.227-230
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• 1997

In this paper, robot navigation experiments with a new navigation algorithm are carried out in real environments. The authors already proposed a reactive navigation algorithm for mobile robots using optimal via-point selection method. At each sampling time, a number of via-point candidates is constructed with various candidates of heading angles and velocities. The robot detects surrounding obstacles, and the proposed algorithm utilizes fuzzy multi-attribute decision making in selecting the optimal via-point the robot would proceed at next step. Fuzzy decision making allows the robot to choose the most qualified via-point even when the two navigation goals-obstacle avoidance and target point reaching-conflict each other. The experimental result shows the successful navigation can be achieved with the proposed navigation algorithm for real environments.

• Proceedings of the KIEE Conference
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• 1996.07a
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• pp.420-425
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• 1996

In this paper a robust speed controller for an induction motor is proposed. The speed controller consists or a fuzzy sliding adaptive controller(FSAC) and a sliding mode torque observer(SMTO). FSAC removes the problem or oscillations caused by discontinuous inputs of the sliding mode controller. The controller also provides robust characteristics against parameter and sampling time variations. Although, however, the performance of FSAC is better than PI controller and fuzzy controller in robustness, it generates the problem of slow response time. To alleviate this problem, a compensator, which performs feedforward control using torque signals produced by SMTO, is added. The simulation and hardware implementation results show that the proposed system is robust to the load disturbance, parameter variations, and measurement noises.

• Proceedings of the KIEE Conference
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• 2006.07d
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• pp.2085-2086
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• 2006

This paper addresses the problem of stability analysis and control synthesis of a digital fuzzy control systems. The authors shows that the stability properties (in the Lyapunov sense) of a digital fuzzy control system can be deduced from the stability properties of the its approximate discretization in the sufficiently small sampling time.