• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.701-706
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• 1998

A design method of rule -based fuzzy modeling is presented for the model identification of complex and nonlinear systems. The proposed rule-based fuzzy modeling implements system structure and parameter identification in the efficient form of " IF..., THEN,," statements. using the theories of optimization and linguistic fuzzy implication rules. The improved complex method, which is a powerful auto-tuning algorithm, is used for tuning of parameters of the premise membership functions in consideration of the overall structure of fuzzy rules. The optimized objective function, including the weighting factors, is auto-tuned for better performance of fuzzy model using training data and testing data. According to the adjustment of each weighting factor of training and testing data, we can construct the optimal fuzzy model from the objective function. The least square method is utilized for the identification of optimum consequence parameters. Gas furance and a sewage treatment proce s are used to evaluate the performance of the proposed rule-based fuzzy modeling.

• Journal of Power Electronics
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• v.18 no.5
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• pp.1369-1379
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• 2018

In this paper, a model predictive torque control (MPTC) without the use of a weighting factor for surface mounted permanent-magnet synchronous machine (SPMSM) drive systems is presented. Firstly, the desired voltage vector is predicted in real time according to the principles of deadbeat torque and flux control. Then the sector of this desired voltage vector is determined. The complete enumeration for testing all of the feasible voltage vectors is avoided by testing only the candidate vectors contained in the sector. This means that only two voltage vectors in the sector need to be tested for selecting the optimal voltage vector in each control period. Thus, the calculation time can be reduced when compared with the conventional enumeration method. On the other hand, a novel cost function that only includes the dq-axis voltage errors between the desired voltage and candidate voltage is designed to eliminate the weighting factor used in the conventional MPTC. Thus, the control complexity caused by the tuning of the weighting factor is effectively decreased when compared with the conventional MPTC. Simulation and experimental investigation have been carried out to verify the proposed method.

• Journal of Korean Society of Rural Planning
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• v.10 no.3 s.24
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• pp.41-51
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• 2004

This study aims to develop a potential evaluation method for urban spatial expansion using remote sensing (RS) and geographic information system (GIS). A multi-criteria evaluation method with several criteria and their weighting values was introduced to evaluate the score and quantification of the potential surface around the existing cities. The six criteria with one geographic factor, slope, and five accessibility factors, time distance from center of the city, national road, interchange of expressway, a big city, and station, were defined for the potential. RS techniques were applied for classification of the actual urban expansion maps between two periods, and GIS functions were used for score of accessibility criteria with a distance decay function from geographic, road and several point maps, which was developed in this study. The new methodology was applied to a test area, Suwon, between 1986 and 1996. In order to optimize the six weighting values, this study made new findings to search the optimal combination of the weighting values from new methodology, weighted scenario method for intensity order (WSM), combined with intensity order and AHP method, including a trial and error method for sensitivity analysis to make the intensity order. The optimal combination of the weighting values by the new method generated the optimal potential surface, considering spatial trend of urban expansion in the test area.

• Journal of the Korea institute for structural maintenance and inspection
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• v.8 no.4
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• pp.153-163
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• 2004

The main objective of this study is to develop a multi-objective fuzzy optimum design program of steel structures and to verify that the multi-objective fuzzy optimum design is more reasonable than the single objective optimum design in real structural design. In the optimization formulation, the objective functions are both total weight and deflection. The design constraints are derived from the ultimate strength of service ability requirement of AISC-LRFD specification. The structural analysis was performed by the finite element method and also considered geometric non-linearity. The different importance of optimum criteria were reflected with two weighting methods ; membership weighting method and objective weighting method. Thus, designers could choose rational optimum solution of structures with application of two weighting methods.

• IE interfaces
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• v.1 no.1
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• pp.17-26
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• 1988

This paper describes a nonlinear goal programming approach to the optimal composition of composite solid propellant taking multiple characteristics into consideration synchronously. The nonlinear goal programming model with response functions, restrictions and the optimal value of each characteristic is developed using Scheffe's "Experiments with mixtures" and preference weighting system. Objective functions are described based on process, performance and assurance characteristics. The systematic approach to optimal composition in this study is proved efficient through a CTPB-AL-AP propellant which is one of composite solid propellant systems.

• International Journal of Control, Automation, and Systems
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• v.1 no.1
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• pp.101-110
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• 2003

This paper introduces an identification method for nonlinear models in the form of rule-based Fuzzy-Neural Networks (FNN). In this study, the development of the rule-based fuzzy neural networks focuses on the technologies of Computational Intelligence (CI), namely fuzzy sets, neural networks, and genetic algorithms. The FNN modeling and identification environment realizes parameter identification through synergistic usage of clustering techniques, genetic optimization and a complex search method. We use a HCM (Hard C-Means) clustering algorithm to determine initial apexes of the membership functions of the information granules used in this fuzzy model. The parameters such as apexes of membership functions, learning rates, and momentum coefficients are then adjusted using the identification algorithm of a GA hybrid scheme. The proposed GA hybrid scheme effectively combines the GA with the improved com-plex method to guarantee both global optimization and local convergence. An aggregate objective function (performance index) with a weighting factor is introduced to achieve a sound balance between approximation and generalization of the model. According to the selection and adjustment of the weighting factor of this objective function, we reveal how to design a model having sound approximation and generalization abilities. The proposed model is experimented with using several time series data (gas furnace, sewage treatment process, and NOx emission process data from gas turbine power plants).

• Journal of Advanced Marine Engineering and Technology
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• v.36 no.1
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• pp.126-132
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• 2012

This paper suggests a design method of the model-following H${\infty}$ control system having robust performance. This H${\infty}$ control system is designed by applying genetic algorithm(GA) with reference model to the optimal determination of weighting functions and design parameter ${\gamma}$ that are given by Glover-Doyle algorithm which can design H${\infty}$ controller in the state space. These weighting functions and design parameter ${\gamma}$ are optimized simultaneously in the search domain guaranteeing the robust performance of closed-loop system. The effectiveness of this H${\infty}$ control system is verified by applying to the boiler-turbine control system.

• Steel and Composite Structures
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• v.25 no.4
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• pp.403-413
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• 2017

The fabric braided braking hose that delivers the driver's braking force to brake cylinder undergoes the large deformation cyclic motion according to the steering and bump/rebound motions of vehicle. The cyclic large deformation of braking hose may give rise to two critical problems: the interference with other adjacent vehicle parts and the micro cracking stemming from the fatigue damage accumulation. Hence, both the hose deformation and the fatigue damage become the critical issue in the design of braking hose. In this context, this paper introduces a multi-objective optimization method for minimizing the both quantities. The total length of hose and the helix angles of fabric braided composite layers are chosen for the design variables, and the maximum hose deformation and the critical fatigue life cycle are defined by the individual single objective functions. The trade-off between two single objective functions is made by introducing the weighting factors. The proposed optimization method is validated and the improvement of initial hose design is examined through the benchmark simulation. Furthermore, the dependence of optimum solutions on the weighting factors is also investigated.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.15 no.10
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• pp.860-869
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• 2003

Design optimization of the heat sink with 7${\times}$7 square pin-fins is performed numerically using the Computational Fluid Dynamics (CFD) and the Computer Aided Optimization (CAO). In the pin-fins heat sink, the optimum design variables for fin height (h), fin width (w), and fan-to-heat sink distance (c) can be achieved when the thermal resistance ($\theta$$_{j}$) at the junction and the overall pressure drop ($\Delta$p) are minimized simultaneously. To complete the optimization, the finite volume method for calculating the objective functions, the BFGS method for solving the unconstrained non-linear optimization problem, and the weighting method for predicting the multi-objective problem are used. The results show that the optimum design variable for the weighting coefficient of 0.5 are as follows: w=4.653 mm, h=59.215 mm, and c=2.667 mm. In this case, the objective functions are predicted as 0.56K/W of thermal resistance and 6.91 Pa of pressure drop. The Pareto optimal solutions are also presented.re also presented.d.

• International Journal of Automotive Technology
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• v.7 no.3
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• pp.309-314
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• 2006

In this paper, the ride comfort from a computer simulation was compared to the experimental result. For measuring ride comfort of a passenger car, acceleration data was obtained from the floor and seat during highway running with different speeds. The measured acceleration components were multiplied by the proper weighting functions, and then summed together to calculate overall ride values. Testing several passenger cars, the ride comforts were compared. In order to investigate the effect of vibration signals on the steering wheel, an apparatus to measure the vibrations and weighting functions on the steering wheel were designed. The effect of the steering accelerations on the ride comfort were investigated and added for the overall ride comfort. For the computer simulations, Korean dummy models were developed based on the Hybrid III dummy models. For the Korean dummy scaling, the national anthropometric survey of Korean people was used. In order to compare and check the validity of the developed Korean dummy models, dynamic responses were compared to those of Hybrid III dummy models. The computer simulation using the MADYMO software was also compared to the experimental results.