• Journal of Electrical Engineering and Technology
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• v.12 no.2
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• pp.621-631
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• 2017

In this paper, we study the various impacts of connecting distributed generation (DG) to the distribution network. The comprehensive evaluation index system (CEIS) of four hierarchies is established, considering economy, reliability and voltage quality, and the calculation methods of different indexes are presented. This paper puts forward an improved triangular fuzzy number analytic hierarchy process (ITFNAHP) to weight the second level indexes (SLI) and the third level indexes (TLI), and calculates the variation coefficient to weight the fourth level indexes (FLI). We calculate the comprehensive weight coefficients based on the weight coefficients of the SLI, TLI and FLI, and then calculate the comprehensive evaluation of satisfaction (CES) of different access schemes. On the basis of the IEEE 33-bus example system, simulations of the calculation methods and the comprehensive evaluation method are carried out under different DG access schemes according to the same total investment cost and the same permeability, respectively, and the simulation results are analyzed and discussed.

• Journal of Digital Contents Society
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• v.9 no.1
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• pp.53-60
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• 2008

Based on similarities between fuzzy set theory and mathematical morphology, Grabish proposed a fuzzy morphology based on the Sugeno fuzzy integral. This paper proposes a fuzzy mathematical morphology based on the defuzzification of the fuzzy measure which corresponds to fuzzy integral. Its process makes a fuzzy set used as a measure of the inclusion of each fuzzy measure for subsets. To calculate such an integral a $\lambda$-fuzzy measure is defined which gives every subsets associated with the universe of discourse, a definite non-negative weight. Fast implementable definitions for erosion and dilation based on the fuzzy measure was given. An application for robust skeletonization of two-dimensional objects was presented. Simulation examples showed that the object reconstruction from their skeletal subsets that can be achieved by using the proposed was better than by using the binary mathematical morphology in most cases.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.4
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• pp.767-778
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• 2003

This paper presents a method for generating optimal fuzzy rules using a genetic algorithm. Fuzzy rules are generated from the training data in the first stage. In this stage, fuzzy c-Means clustering method and cluster validity are used to determine the structure and initial parameters of the fuzzy inference system. A cluster validity is used to determine the number of clusters, which can be the number of fuzzy rules. Once the structure is figured out in the first stage, parameters relating the fuzzy rules are optimized in the second stage. Weights and variance parameters are tuned using genetic algorithms. Variance parameters are also managed with left and right for asymmetrical Gaussian membership function. The method ensures convergence toward a global minimum by using genetic algorithms in weight and variance spaces.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.2
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• pp.228-236
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• 2012

In this paper, a controller for two wheeled inverted pendulum robot is designed to have more stable balancing capability than conventional controller. Fuzzy control structure is chosen for the two wheeled inverted pendulum robot, and fuzzy membership function factors for the controller are obtained for specified 3 users' weights using trial-and-error method. Next a neural network is employed to generate fuzzy membership function factors for more stable control performance when the user's weight is arbitrarily selected. Through the simulation study we find that the designed fuzzy controller using the neural network is superior to the conventional fuzzy controller.

• Journal of the Korean Society for Precision Engineering
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• v.28 no.4
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• pp.391-397
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• 2011

Control of interior permanent magnet (IPMSM) is difficult because its nonlinearity and parameter uncertainty. In this paper, a fuzzy c-regression models clustering algorithm which is based on T-S fuzzy is used to model IPMSM with a series linear model and weight them by memberships. Lagrangian of constrained function is built for calculating clustering centers where training output data are considered. Based on these clustering centers, least square method is applied for T-S fuzzy linear model parameters. As a result, IPMSM can be modeled as T-S fuzzy model for T-S fuzzy control of them.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2006.05a
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• pp.309-314
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• 2006

Interior permanent magnet synchronous motor(IPMSM) has become a popular choice in electric vehicle applications, due to their excellent power to weight ratio. This paper proposes maximum torque control of IPMSM drive using adaptive learning fuzzy neural network and artificial neural network. This control method is applicable over the entire speed range which considered the limits of the inverter's current md voltage rated value. For each control mode, a condition that determines the optimal d-axis current $i_d$ for maximum torque operation is derived. This paper considers the design and implementation of novel technique of high performance speed control for IPMSM using adaptive teaming fuzzy neural network and artificial neural network. The hybrid combination of neural network and fuzzy control will produce a powerful representation flexibility and numerical processing capability. Also, this paper proposes speed control of IPMSM using adaptive teaming fuzzy neural network and estimation of speed using artificial neural network. The back propagation neural network technique is used to provide a real time adaptive estimation of the motor speed. The proposed control algorithm is applied to IPMSM drive system controlled adaptive teaming fuzzy neural network and artificial neural network, the operating characteristics controlled by maximum torque control are examined in detail. Also, this paper proposes the analysis results to verify the effectiveness of the adaptive teaming fuzzy neural network and artificial neural network.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.1
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• pp.8-14
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• 2013

In this paper, a control system for two wheeled inverted pendulum robot is implemented to have more stable balancing capability than the conventional control system. Fuzzy control structure is chosen for the two wheeled inverted pendulum robot, and fuzzy membership function factors for the control system are obtained for 3 specified weights using a trial-and-error method. Next a neural network is employed to generate fuzzy membership function factors for more stable control performance when the weight is arbitrarily selected. Through some experiments, we find that the proposed fuzzy control system using the neural network is superior to the conventional fuzzy control system.

• Journal of Korea Port Economic Association
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• v.28 no.2
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• pp.29-41
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• 2012

Competition between international Hub ports has been more and more intense. In order to invigorate itself, Gwang-Yang port has been making multilateral efforts. However, it has not still reached 300Millions TEU which is the standard to be permitted as a self-reliance Hub port. Therefore, a functional modification of berth should be considered. This study suggests to transform container berths to general berths. This article is focused on reserve berth mode of Gwang Yang hub port and selected three kinds of berths as alternative subjects of the study: general berth, exclusive berth, and multipurpose berth. This research has conducted that The subjects of the survey were in relation with Logistics as professional mutually group about Gwang-Yang hub port. The measurements of this survey were measure section and factor. Also, Fuzzy AHP(Analytic Hierarchy Process) was applied to the survey. According to the result, by measuring weight values of alternatives, the best favored one was multipurpose berth expect stability (32.6%), Exclusive berth was graded the most among the alternatives. Also, based on total weight value, the order of priority is as follows: multipurpose berth(38.2%), exclusive port(33.7%), general berth(28.1%).

• Computers and Concrete
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• v.19 no.6
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• pp.617-623
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• 2017

This work is conducted with the aim of using waste material to reserve the natural resources. The objective is accomplished by conducting experimentation and verify by modeling based on fuzzy logic. In experimentation, concrete is casted by using natural/river sand as fine aggregate and termed as control specimen. Natural sand is conserved by replacing it with used foundry sand (UFS) by an amount of 10, 20 and 30% by weight. Fresh and hardened properties of concrete are investigated at different ages. It is observed that compressive strength and modulus of elasticity reduced with the increase in amount of UFS. Furthermore, concrete compressive strength is predicted by using fuzzy logic model and verified at different replacement ratio and age with experimental observations.

• Proceedings of the Korean Society For Composite Materials Conference
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• 2000.04a
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• pp.143-148
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• 2000

In this article, we presents multi-objective design optimization of laminated composite beam using Fuzzy programming method. At first, the two design objectives are minimizing the structural weight and maximizing the buckling load respectively. Fuzzy multi-optimization problem can be formulated based on results of single optimizations. Due to different relative importance of design objectives, membership functions are constructed by adding exponential parameters for different objective's weights. Finite element analysis of composite beam for buckling behavior are carried by Natural mode method proposed by J.Argyris and computational time of analysis can be reduced. With this scheme, a designer can conveniently obtain a compromise optimal solution of a multi-objective optimization problem only by providing some exponential parameters corresponding to the importance of the objective functions.