• Proceedings of the KIEE Conference
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• 1993.07a
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• pp.383-386
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• 1993

In this paper, we propose a sensory data combination method by a fuzzy number approach for multisensor data fusion. Generally, the weighting of one sensory data with respect to another is derived from measures of the relative reliabilities of the two sensory modules. But the relative weight of two sensory data can be approximately determined through human experiences or insufficient experimental data without difficulty. We represent these relative weight using appropriate fuzzy numbers as well as sensory data itself. Using the relative weight, which is subjective valuation, and a fuzzy-numbered sensor data, the fuzzy weighted average method is used for a representative sensory data. The manipulation and calculation of fuzzy numbers can be carried out using the Zadeh's extension principle which can be approximately implemented by the $\alpha$-cut representation of fuzzy numbers and interval analysis.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.05a
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• pp.1012-1016
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• 2002

This paper describes a research work of developing computer-aided design of a product with bending and piercing for progressive working. An approach to the system for progressive working is based on the knowledge-based rules. Knowledge for the system is formulated from plasticity theories, experimental results and the empirical knowledge of field experts. The system has been written in Auto-LISP on the Auto-CAD with a personal computer and is composed of four main modules, which are input and shape treatment, flat pattern layout, strip layout, and die layout modules. The system is designed by considering several factors, such as bending sequences by fuzzy set theory, complexities of blank geometry, punch profiles, and the availability of a press equipment. Strip layout drawing generated in the strip layout module is presented in 3-D graphic forms, including bending sequences and piercing processes with punch profiles divided into for external area. The die layout module carries out die design for each process obtained from the results of the strip layout. Results obtained using the modules enable the manufacturer for progressive working of electric products to be more efficient in this field.

• Computers and Concrete
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• v.15 no.1
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• pp.55-71
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• 2015

This paper presents a novel harmony search (HS)-based data-driven single input rule modules (SIRMs)-connected fuzzy inference system (FIS) for the prediction of stress in externally prestressed tendon. The proposed method attempts to extract causal relationship of a system from an input-output pairs of data even without knowing the complete physical knowledge of the system. The monotonicity property is then exploited as an additional qualitative information to obtain a meaningful SIRMs-connected FIS model. This method is then validated using results from test data of the literature. Several parameters, such as initial tendon depth to beam ratio; deviators spacing to the initial tendon depth ratio; and distance of a concentrated load from the nearest support to the effective beam span are considered. A computer simulation for estimating the stress increase in externally prestressed tendon, ${\Delta}f_{ps}$, is then reported. The contributions of this paper is two folds; (i) it contributes towards a new monotonicity-preserving data-driven FIS model in fuzzy modeling and (ii) it provides a novel solution for estimating the ${\Delta}f_{ps}$ even without a complete physical knowledge of unbonded tendons.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.29 no.2
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• pp.27-32
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• 2015

A maximum power point tracking (MPPT) algorithm using fuzzy controller was considered. MPPT method was implemented based on the voltage and reference PV voltage value was obtained from Artificial Neural Network (ANN)-model of PV modules. Therefore, measuring only the PV module voltage is adequate for MPPT operation. Fuzzy controller is used to directly control dc-dc buck converter. The simulation results have been used to verify the effectiveness of the algorithm. The proposed method is compared with conventional PO(perturbation & observation), IC(Incremental Conductance) method. The nonlinearity and adaptiveness of fuzzy controller provided good performance under parameter variations such as solar irradiation.

• Journal of the Korean Society for Precision Engineering
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• v.19 no.1
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• pp.79-92
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• 2002

This paper describes a research work of developing computer-aided design of a product with bending and piercing for progressive working. An approach to the system for progressive working is based on the knowledge-based rules. Knowledge for the system is formulated from plasticity theories, experimental results and the empirical knowledge of field experts. The system has been written in AutoLISP on the AutoCAD with a personal computer and is composed of four main modules, which are input and shape treatment, flat pattern layout, strip layout and die layout modules. The system is designed by considering several factors, such as bending sequences by fuzzy set theory, complexities of blank geometry, punch profiles, and the availability of a press equipment. Strip layout drawing generated in the strip layout module is presented in 3-D graphic farms, including bending sequences and piercing processes with punch profiles divided into for external area. The die layout module carries out die design for each process obtained from the results of the strip layout. Results obtained using the modules enable the manufacturer for progressive working of electric products to be more efficient in this field.

• Proceedings of the KIEE Conference
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• 1991.07a
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• pp.781-786
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• 1991

This paper introduces a new methodology for multisensor data fusion. The method makes use of fuzzy techniques and possibility distribution as a fuzzy restriction which acts as an elastic constraint on the values that may be assigned to a variable. We propose a simple sensor fuzzy modeling method which can be used for cluster validity analysis. As a result, the feasibility of these multisensor data fusion modules is demonstrated by computer simulation applicable to the problem of object identification.

• Journal of the Korean Solar Energy Society
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• v.24 no.2
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• pp.89-96
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• 2004

PV system is easy to operate and maintain than the other power generating system since it generally contains no moving parts, operates silently and requires very little maintenance. A solar cell generates DC power from sunlight whose power is different at any instance according to condition of irradiation and temperature variables. In order to improve the system utility factor and efficiency of energy conversion, it is desirable to operate the PV system at maximum power point of solar cell under different condition This paper describes the experimental results of the PV system contain solar modules and a DC-DC converter(boost type chopper) using fuzzy controller. The experimental results show that the PV system always operates at maximum power point of solar cells having stabilized output voltage waveform with relatively small ripple component.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.575-579
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• 2005

In this paper, the development of an IMM(Injection Molding Machine) controller is discussed. Presently, the Mold Close and Open Control Method of a toggle-type IMM is open-loop control. Through the development, a PC based control system was built instead of an existing controller and a closed-loop control replaced the previous control method by using PC based PLC. To control the nonlinear system of toggle type clamping unit, a fuzzy PI control algorithm was selected and it was programmed by an IL(Instruction List) and a LD(Ladder Diagram) on a PC based PLC. The application of fuzzy algorithm as the control method was also considered to change a control object like a mold replacement or an additional apparatus. For the development of an IMM controller, PC based PLC of PCI card type, distributed I/O modules with CANopen and Industrial PC and HMI (Human Machine Interface) software were used.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.03a
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• pp.116-119
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• 1998

Abstract-In paper, an operation support software for combustion control of refuse incineration plant is developed using fuzzy model and genetic algorithm. It has two major modules which are simulation module and optimal operation module. In simulation module modelling is performed to obtain fuzzy model of the refuse incineration plant and obtained fuzzy model predicts outputs of the plant when inputs are given. This module can be used to obtain control strategy, and train and enhance operators' skill by simulating the plant. And in optimal operation module, genetic algorithm searches and finds out optimal control inputs over all possible solutions in respect to desired outputs. In order to testify proposed operation support software, computer simulation was carried out.

• International Journal of Control, Automation, and Systems
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• v.1 no.3
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• pp.321-331
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• 2003

Experimental software datasets describing software projects in terms of their complexity and development time have been the subject of intensive modeling. A number of various modeling methodologies and modeling designs have been proposed including such approaches as neural networks, fuzzy, and fuzzy neural network models. In this study, we introduce the concept of the Rule-based fuzzy polynomial neural networks (RFPNN) as a hybrid modeling architecture and discuss its comprehensive design methodology. The development of the RFPNN dwells on the technologies of Computational Intelligence (CI), namely fuzzy sets, neural networks, and genetic algorithms. The architecture of the RFPNN results from a synergistic usage of RFNN and PNN. RFNN contribute to the formation of the premise part of the rule-based structure of the RFPNN. The consequence part of the RFPNN is designed using PNN. We discuss two kinds of RFPNN architectures and propose a comprehensive learning algorithm. In particular, it is shown that this network exhibits a dynamic structure. The experimental results include well-known software data such as the NASA dataset concerning software cost estimation and the one describing software modules of the Medical Imaging System (MIS).