• Journal of the Korean Society of Industry Convergence
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• v.20 no.1
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• pp.34-48
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• 2017

This study proposes a new approach to control a trajectory control of vertical type articulated robot arm with six revolution joints by computed torque method for manufacturing process automation. The proposed control scheme takes advantage of the properties of the fuzzy controllers. The proposed method is suitable to control of the trajectory and path control in cartesian space for vertical type articulated robot manipulator for forging manufacturing process automation. The results is illustrated that the proposed fuzzy computed torque controller is more stable and robust than the conventional computed torque controller. This study is included with an analytical methodology of inverse kinematic computation for 6 DOF manipulators. And an intelligent PID based on feed forward fuzzy control structure is applied to control the working path control with disturbances caused by uncertainty parameters of the manipulator dynamic model. Lastly, the validity of proposed is verified by simulations and experiments.

• Journal of the Institute of Convergence Signal Processing
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• v.11 no.1
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• pp.88-91
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• 2010

In this paper, We are composed the position recognition and speed control using the moving robot in the shield Room with a RF Module and Ultrasonic Sensors. Double look up tables are selected a reference value/duty ratio. The moving robot with the dual fuzzy rules which can decrease a Conversion time than basic fuzzy control rules at start point and curve region. Also, a changing times of double look up table are rise at specific points b1,c1,d1 in the e-${\Delta}e$ phase plane and the one of the look up table is used which for increase rising time at transition area, the other used for rapidly conversion to the reference value. We verified that a dual fuzzy control rules get the good response compare with the basic fuzzy control rule.

• Journal of the Institute of Electronics Engineers of Korea TE
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• v.39 no.3
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• pp.97-104
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• 2002

In this paper we describe the method which optimizes the partition of the input space by means of measure of fuzziness for fuzzy neural network. It covers its generation of fuzzy rules for input sub space. It verifies the performance of the system depended on the various time interval of the input. This method divides the input space into several fuzzy regions and assigns a degree of each of the generated rules for the partitioned subspaces from the given data using the Shannon function and fuzzy entropy function generating the optimal knowledge base without the irrelevant rules. In this scheme the basic idea of the fuzzy neural network is to realize the fuzzy rule base and the process of reasoning by neural network and to make the corresponding parameters of the fuzzy control rules be adapted by the steepest descent algorithm. According to the input interval the proposed inference procedure proves that the fast convergence of root mean square error (RMSE) owes to the optimal partition of the input space

• Journal of the Korea Convergence Society
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• v.9 no.7
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• pp.231-240
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• 2018

Automobile industry is facing a variety of risks, including the rise of international oil price and the increase of car prices. In addition to the government's deregulation, efforts should be made to improve management aiming at higher production efficiency. In this study, we established a model for evaluating the procurement logistics based on the Fuzzy-AHP-TOPSIS by using the factors that are actually used in real companies aimed at the improvement of procurement logistics. A total of three automobile factories of Company G were chosen as the evaluation subject. In the result of the Fuzzy-AHP analysis that was conducted on a sample of three car factories, solving the long-term quality problems, minimizing the stop time due to the shortage of materials, preventing the of equipment accident, and solving the short-term quality problems were proven to be the most important factors. TOPSIS analysis result indicated that Factory B had the best procurement logistics. Our study has significance that it can contribute to the improvement of efficiency in the automobile industry as the evaluation model suggested in this study can be used for regular evaluation related to the procurement logistics in the future.

• Journal of information and communication convergence engineering
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• v.4 no.4
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• pp.174-179
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• 2006

In this paper we present a text detection method inspired by wavelet packet analysis and improved fuzzy clustering algorithm(IAFC).This approach assumes that the text and non-text regions are considered as two different texture regions. The text detection is achieved by using wavelet packet analysis as a feature analysis. The wavelet packet analysis is a method of wavelet decomposition that offers a richer range of possibilities for document image. From these multi scale features, we adapt the improved fuzzy clustering algorithm based on the unsupervised learning rule. The results show that our text detection method is effective for document images scanned from newspapers and journals.

• Journal of information and communication convergence engineering
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• v.6 no.4
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• pp.421-424
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• 2008

In torque transmission system, we must suppressed vibration for Accuracy characteristic response of motor, Therefore, vibration suppression factor is very important motor control. To suppress vibration, a various control method has been proposed. Specially, one method of vibration suppression used disturbance observer filter. This method is torsion torque passing disturbance observer filter. By the estimated torsion torque feedback, vibration can be suppressed. The CDM(coefficient diagram method) is used to design the filter and Proportional controller. But using coefficient diagram method, not adapted controller parameter in disturbance. For this solution, we used fuzzy controller for auto tuning controller parameter. We proved this approach is confirmed by simulation.

• Journal of information and communication convergence engineering
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• v.8 no.1
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• pp.19-22
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• 2010

A finger language helping hearing impaired people in communication A sign language helping hearing impaired people in communication is not popular to ordinary healthy people. In this paper, we propose a method for real-time sign language recognition from a vision system using color information and fuzzy clustering system. We use YCbCr color model and canny mask to decide the position of hands and the boundary lines. After extracting regions of two hands by applying 8-directional contour tracking algorithm and morphological information, the system uses FCM in classifying sign language signals. In experiment, the proposed method is proven to be sufficiently efficient.

• Communications of the Korean Mathematical Society
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• v.28 no.2
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• pp.243-267
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• 2013

This paper is dedicated to study a new class of general nonlinear random A-maximal $m$-relaxed ${\eta}$-accretive (so called (A, ${\eta}$)-accretive [49]) equations with random relaxed cocoercive mappings and random fuzzy mappings in $q$-uniformly smooth Banach spaces. By utilizing the resolvent operator technique for A-maximal $m$-relaxed ${\eta}$-accretive mappings due to Lan et al. and Chang's lemma [13], some new iterative algorithms with mixed errors for finding the approximate solutions of the aforesaid class of nonlinear random equations are constructed. The convergence analysis of the proposed iterative algorithms under some suitable conditions are also studied.

• Journal of information and communication convergence engineering
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• v.15 no.1
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• pp.49-52
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• 2017

Ganglion cysts are benign soft tissues usually encountered in the wrist. In this paper, we propose a method to extract a ganglion cyst region from ultrasonography images by using image segmentation. The proposed method using the possibilistic c-means (PCM) clustering method is applicable to ganglion cyst extraction. The methods considered in this thesis are fuzzy stretching, median filter, PCM clustering, and connected component labeling. Fuzzy stretching performs well on ultrasonography images and improves the original image. Median filter reduces the speckle noise without decreasing the image sharpness. PCM clustering is used for categorizing pixels into the given cluster centers. Connected component labeling is used for labeling the objects in an image and extracting the cyst region. Further, PCM clustering is more robust in the case of noisy data, and the proposed method can extract a ganglion cyst area with an accuracy of 80% (16 out of 20 images).

• Journal of Integrative Natural Science
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• v.12 no.4
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• pp.105-115
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• 2019

In this paper, a prediction system is proposed to control the brightness of smart street lamps by predicting the moving path through the reduction of consumption power and information of pedestrian's past moving direction while meeting the function of existing smart street lamps. The brightness of smart street lamps is adjusted by utilizing the walk tracking vector and soft hand-off characteristics obtained through the motion sensing sensor of smart street lamps. In addition, the motion vector is used to analyze and predict the pedestrian path, and the GPU is used for high-speed computation. Pedestrians were detected using adaptive Gaussian mixing, weighted difference imaging, and motion vectors, and motions of pedestrians were analyzed using the extracted motion vectors. The preprocessing process using linear interpolation is performed to improve the performance of the proposed prediction system. Fuzzy prediction system and neural network prediction system are designed in parallel to improve efficiency and rough set is used for error correction.