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REFERENCE LINKING PLATFORM OF KOREA S&T JOURNALS
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Journal of Korean Institute of Intelligent Systems
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Journal DOI :
Korean Institute of Intelligent Systems
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Volume & Issues
Volume 8, Issue 6 - Nov 1998
Volume 8, Issue 5 - Oct 1998
Volume 8, Issue 4 - Aug 1998
Volume 8, Issue 3 - Jun 1998
Volume 8, Issue 2 - Apr 1998
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Identification of Tracking Conduct Wiring Using Neural Networks
Journal of Korean Institute of Intelligent Systems, volume 8, issue 2, 1998, Pages 1~8
In this paper, a method which cna detect tracking caused by the insulation deterioration of conduct wiring, is proposed. To investigate it, we analyzed the harmonics of each load current waveform and those of tracking current waveform with FFT. The computer which take experiment data is learned by neural network algorithm, which has recently been used for the load recognition. The proposed metod in our study can be applied to the development of several measuring equipments such as hotline insulation tester, cna earch tester for the detection of tracking under hot-line state, Furthermore, it can substitutes molded case circuit breaker, fuse, and so on.
A Study on the Pattern Recognition based Distance Protective Relaying Scheme in Power System
Journal of Korean Institute of Intelligent Systems, volume 8, issue 2, 1998, Pages 9~20
In this paper, a new distance relaying scheme is proposed. Artificial neural networks are applied to the distance relaying system composed of pattern recognition based. The proposed distance relaying scheme has two blocks of pattern recognition stages to estimate the fundamental frequency and to classify the fault types. In the first block, a filtering method using neural networks called a neural networks mapping filter(NMF) is presented to efficiently extract the features. And in the sec'ond block, the estimator called neural networks fault pattern estimator(NFPE) is also presented to classify the fault types by the extracted effective features obtained from NMF. Each block of these applied schemes is trained by back-propagation algorithm of multilayer perceptron and show the fast and accurate pattern recognition by ability of multilayer neural networks. The test result of this approach are obtained the good performance from the fault transient wave signals of EMTP(e1ectromagnetic transients program) in the various fault conditions of power systems. Key Word : Pattern Recognition, Distance Relaying, Mapping Filter, Fault Pattern Estimator, Back-Propagation Algorithm
A Self-Organizing Fuzzy Logic Controller with a Performance Evaluation Level
Journal of Korean Institute of Intelligent Systems, volume 8, issue 2, 1998, Pages 21~34
[n this paper, we propose a hierarchical self-organizing fuzzy logic controller to improve the performance of the FARMA(Fuzzy auto-regressive moving average) SOC(Self-organizing fuzzy logic controller) when the system parameters change. The proposed controller contains the FARMA SC)C in the lower level and has a coordinator in the higher level, which evaluates convergence. and when it senses the degradation of system performance it compensates the control input by a look-up table. The proposed controller shows good perforniance over the FARMA SOC when the system parameters change. We executed some computer simulations on the regulation problem of an inlrerted pendulum system and compared the results with those of the FARMA SOC. As a result, it ha:; been shown that the proposed controller outperformed the FARMA SOC when the changes of the system parameters occurred.
Fuzzy Logic-based Navigation Strategy of Mobile Robots with Obstacle Avoidance
Journal of Korean Institute of Intelligent Systems, volume 8, issue 2, 1998, Pages 35~42
High-Frequency Induction Heating System Design of a PFM and PWM method using Fuzzy Control
Journal of Korean Institute of Intelligent Systems, volume 8, issue 2, 1998, Pages 43~49
This paper describes a phase-shift pulse-width modulation and pulse-frequency modulation seriesresonant high-frequency inverter using IGBT for the power control of high-frequency inductionheating using fuzzy, which is practically applied for 2 0- 5~0 0~~ ~in 1d uction-heating and meltingpov~er supply in industrial fields. The adaptive frequency tracking based phase-shifting PWMregillation scheme is presented in order to minimize switching losses. The trially-producedbreadboards using IGBT are succesfully demostrated and discussed.discussed.
Load Frequency Control using Parameter Self-Tuning fuzzy Controller
Journal of Korean Institute of Intelligent Systems, volume 8, issue 2, 1998, Pages 50~59
This paper presents stabilization and adaptive control of flexible single link robot manipulator system by self-recurrent neural networks that is one of the neural networks and is effective in nonlinear control. The architecture of neural networks is a modified model of self-recurrent structure which has a hidden layer. The self-recurrent neural networks can be used to approximate any continuous function to any desired degree of accuracy and the weights are updated by feedback-error learning algorithm. When a flexible manipulator is rotated by a motor through the fixed end, transverse vibration may occur. The motor toroque should be controlled in such a way that the motor rotates by a specified angle, while simultaneously stabilizing vibration of the flexible manipuators so that it is arresed as soon as possible at the end of rotation. Accurate vibration control of lightweight manipulator during the large changes in configuration common to robotic tasks requires dynamic models that describe both the rigid body motions, as well as the flexural vibrations. Therefore, a dynamic models for a flexible single link robot manipulator is derived, and then a comparative analysis was made with linear controller through an simulation and experiment. The results are proesented to illustrate thd advantages and imporved performance of the proposed adaptive control ove the conventional linear controller.
A Study on Fuzziness Parameter Selection in Fuzzy Vector Quantization for High Quality Speech Synthesis
Journal of Korean Institute of Intelligent Systems, volume 8, issue 2, 1998, Pages 60~69
This paper proposes a speech synthesis method using Fuzzy VQ, and then study how to make choice of fuzziness value which optimizes (controls) the performance of FVQ in order to obtain the synthesized speech which is closer to the original speech. When FVQ is used to synthesize a speech, analysis stage generates membership function values which represents the degree to which an input speech pattern matches each speech patterns in codebook, and synthesis stage reproduces a synthesized speech, using membership function values which is obtained in analysis stage, fuzziness value, and fuzzy-c-means operation. By comparsion of the performance of the FVQ and VQ synthesizer with simmulation, we show that, although the FVQ codebook size is half of a VQ codebook size, the performance of FVQ is almost equal to that of VQ. This results imply that, when Fuzzy VQ is used to obtain the same performance with that of VQ in speech synthesis, we can reduce by half of memory size at a codebook storage. And then we have found that, for the optimized FVQ with maximum SQNR in synthesized speech, the fuzziness value should be small when the variance of analysis frame is relatively large, while fuzziness value should be large, when it is small. As a results of comparsion of the speeches synthesized by VQ and FVQ in their spectrogram of frequency domain, we have found that spectrum bands(formant frequency and pitch frequency) of FVQ synthesized speech are closer to the original speech than those using VQ.
A Cost-Effective and Accurate COA Defuzzifier Without Multipliers and Dividers
Journal of Korean Institute of Intelligent Systems, volume 8, issue 2, 1998, Pages 70~81
This paper proposes an accurate and cost-effective COA defuzzifier of fuzzy logic controller (FLC). The accuracy of the proposed COA defuzzifier is obtained by involving both membership values and spans of membership functions in calculating a crisp value. The cost-effectiveness of the proposed COA defuzzifier is obtained by replacing the division in the COA defuzzifier by finding an equilibrium point of both the left and right moments. The proposed COA defuzzifier has two disadvantages that it ncreases the hardware complexity due to the additional multipliers and it takes a lot of computation time to find the moment equilibrium point. The first disadvantage is overcome by replacing the multipliers with the stochastic AND operations. The second disadvantage is alleviated by using a coarse-to-fine searching algorithm that accelerates the finding of moment equilibrium point. Application of the proposed COA defuzzifier to the truck backer-upper control problem is performed in the VHDL simulation and the control accuracy of the proposed COA defuzzifier is compared with that of the conventional COA defuzzifier in terms of average tracing distance.
Text-Independent Speaker Identification System Using Speaker Decision Network Based on Delayed Summing
Journal of Korean Institute of Intelligent Systems, volume 8, issue 2, 1998, Pages 82~95
In this paper, we propose a text-independent speaker identification system which has a classifier composed of two parts; to calculate the degree of likeness of each speech frame and to select the most probable speaker from the entire speech duration. The first part is realized using RBFN which is selforganized through learning and in the second part the speaker is determined using a con-tbination of MAXNET and delayed summings. And we use features from linear speech production model and features from fractal geometry. Closed-set speaker identification experiments on 13 male homogeneous speakers show that the proposed techniques can achieve the identification ratio of 100% as the number of delays increases.
Reusability Decision Generation system using Rough Set
Journal of Korean Institute of Intelligent Systems, volume 8, issue 2, 1998, Pages 96~105
Design of an Automatic constructed Fuzzy Adaptive Controller(ACFAC) for the Flexible Manipulator
Journal of Korean Institute of Intelligent Systems, volume 8, issue 2, 1998, Pages 106~116
A position control algorithm of a flexible manipulator is studied. The proposed algorithm is based on an ACFAC(Automatic Constructed Fuzzy Adaptive Controller) system based on the neural network learning algorithms. The proposed system learns membership functions for input variables using unsupervised competitive learning algorithm and output information using supervised outstar learning algorithm. ACFAC does not need a dynamic modeling of the flexible manipulator. An ACFAC is designed that the end point of the flexible manipulator tracks the desired trajectory. The control input to the process is determined by error, velocity and variation of error. Simulation and experiment results show a robustness of ACFAC compared with the PID control and neural network algorithms.
Stabilization Power Systems withan Adaptive Fuzzy Control
Journal of Korean Institute of Intelligent Systems, volume 8, issue 2, 1998, Pages 117~127
Power systems have uncertain dynamics due to a variety of effects such as lightning, severe storms and equipment failures. The variation of the effective reactance of a transmission line due to a fault is an example of uncertainty in power system dynamics. Hence, a robust controller to cope with these uncertainties is needed. Recently, fuzzy controllers are becoming quite popular for robust control due to its potential of dealing with uncertain systems. Thus in this paper we design an adaptive fuzzy controller based on an input-output linearization approach for the transient stabilization and voltage regulation of a power system under a sudden fault. Also this paper proposes a fuzzy system that estimates the upper bound of uncertain term in the system dynamics to guarantee the Lyapunov stability. Simulation results show that good performance is achieved by the proposed controller.
Construction of moving object tracking framework with fuzzy clustering, prediction and Hausdorff distance
Journal of Korean Institute of Intelligent Systems, volume 8, issue 2, 1998, Pages 128~133
In this paper, we present a parallel framework for tracking moving objects. Parallel framework consists largely of two parts:Search Space Reduction(SSR) and Tracking(TR). SSR is further composed of fuzzy clustering and prediction based on Kalman filter. TR is done by boundarymatching using the Hausdorff distance based on distance transform.
Fuzzy Sensor Algorithm for Measuring Traffic Information
Journal of Korean Institute of Intelligent Systems, volume 8, issue 2, 1998, Pages 134~141
Sometimes we need to acquire symbolic quantity of information instead of physical quantity for the output of any system. For instance we can not control traffic signal accurately through only the number of vehicles. At that case we can produce better output using symbolic quantity of road length and width and vehicle type. But it is very difficult to aggregate symbolic information from the unrelated and mutually conflicted input after calculating linear and related expression. Moreover that will take much time to produce symbolic output by the physical quantity only. In this paper we implemented the ultimate traffic control information by using fuzzy sensor algorithm and compared our results with the conventional traffic controller after studying the necessity of symbolic information in the traffic control.