• Proceedings of the KIEE Conference
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• 1999.07g
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• pp.2911-2913
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• 1999

This paper suggest an optimal identification method to complex and nonlinear system modeling that is based on Fuzzy-Neural Network(FNN). The FNN modeling implements parameter identification using HCM algorithm and optimal identification algorithm structure combined with two types of optimization theories for nonlinear systems, we use a HCM Clustering Algorithm to find initial parameters of membership function. The parameters such as parameters of membership functions, learning rates and momentum coefficients are adjusted using optimal identification algorithm. The proposed optimal identification algorithm is carried out using both a genetic algorithm and the improved complex method. Also, an aggregate objective function(performance index) with weighted value is proposed to achieve a sound balance between approximation and generalization abilities of the model. To evaluate the performance of the proposed model, we use the time series data for gas furnace, the data of sewage treatment process and traffic route choice process.

• Wind and Structures
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• v.29 no.2
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• pp.99-110
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• 2019

This paper provides a simple numerical method to determine the optimal parameters of tuned mass damper (TMD) and viscoelastic dampers (VEDs) in frame structure for wind vibration control considering the soil-structure interation (SSI) effect in frequency domain. Firstly, the numerical model of frame structure equipped with TMD and VEDs considering SSI effect is established in frequency domain. Then, the genetic algorithm (GA) is applied to obtain the optimal parameters of VEDs and TMD. The optimization process is demonstrated by a 20-storey frame structure supported by pile group for different soil conditions. Two wind resistant systems are considered in the analysis, the Structure-TMD system and the Structure-TMD-VEDs system. The example proves that this method can quickly determine the optimal parameters of energy dissipation devices compared with the traditional finite element method, thus is practically valuable.

• Journal of Advanced Marine Engineering and Technology
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• v.3 no.1
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• pp.19-31
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• 1979

Recently the adaptive control system, which keeps the control system always optimal by adjusting the control parameters automatically according to the variations of the plant parameters, have become very important in the field of control engineering. The adaptive control systems are usally composed of the plant identification, the decision of the optimal control parameters, and the adjustment of the control parameters. This paper deals with a method of the adaptive control system when PI or PID controller is used in the feed back control system. Its controlled object (the plant) is assumed to be described by the transfer function of $\frac{ke^{-LS}}{1+TS}$ where k, T and L are steady state gain, time constant and pure dead time respectively, and their values are variable in accordance with the change of environmental circumstance. It has been known that a pseudo-random binary signal is quite effective for the measurement of an impulse response of a plant. In adaptive control systems, however, the impulse response itself is not appropriate to determine the control parameters. In this paper, the authors propose a method to estimate directly the parameters of the plant k, T and L by means of the correlation technique using 3 level M-sequence signal as a test signal. The authors also propose a method to determine the optimal parameters of the PI or PID controller in the sense of minimizing the square integral of the control error in the feed back control system, and the values of the optimal parameters are computed numerically for various values of T and L, and the results are examined and compared with those of the conventional methods. Finally the above-mentioned two methods are combined and an algorithm to struct an adaptive control system is suggested. The experiments for the indicial responses by means of both the model of the temperature control system using SCR actuater and the analog simulations have shown good results as expected, and the effectiveness of the proposed method is verified. The M-sequence generator and the time delay circuit, which are manufactured for the experiments, are operated in quite a good condition.

• Proceedings of the KSME Conference
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• 2004.11a
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• pp.1028-1033
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• 2004

The heat and flow characteristics in a single-phase parallel-flow heat exchanger was examined numerically to obtain its optimal shape. A response surface method was introduced to predict its performance approximately with respect to design parameters over design domain. Design parameters are inflow and outflow angle of the working fluid and horizontal and vertical location of inlet and outlet. The evaluation of the relative priority of the design parameters was performed to choose three important parameters in order to use a response surface method. A JF factor was used as an evaluation characteristic value to consider the heat transfer and the pressure drop simultaneously. The JF factor of the optimum model, compared to that of the base model, was increased by about 5.3%.

• Journal of the Korean Society for Precision Engineering
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• v.15 no.12
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• pp.14-20
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• 1998

Cutting fluid is a factor which has big effects on both machinability and environment in machining process. The loss of cutting fluids may be reduced by the optimization of machining parameters in process planning. In this study, the environmental impact of fluid loss is analyzed. The fluid loss models in milling process are constructed with the machining parameters. The models are utilized to obtain the optimal machining parameters to minimize the fluid loss. The factors with significant effects on the fluid loss are analyzed by ANOVA test. Finally, optimal parameters are suggested considering both machining economics and environmental impact. This study is expected to be used as a part of a framework for the environmental impact assessment of machining process.

• Journal of Environmental Science International
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• v.24 no.7
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• pp.939-946
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• 2015

Hydraulic conductivity is an important parameter in the analytical model of groundwater. This study analyzed the groundwater movement characteristics by estimating optimal parameters according to hydraulic conductivity input methods with the MODFLOW model which is widely used. It first estimated the optimal parameters by dividing hydraulic conductivity zones by attitude. Next, it estimated optimal parameters by geological characteristic. It analyzed the groundwater movement characteristics by applying the recharge quantity and amount of evapotranspiration of drought periods and flood years with the estimated parameters. As the result was analyzed that there are differences of observation water level values according to hydraulic conductivity input methods but there is no big differences of overall groundwater movement characteristics by hydraulic conductivity input method, the two methods have found to be applicability in analyses of groundwater. So, it is judged that studies on more exact application of hydraulic conductivity and the application methods are needed.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 1994.11a
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• pp.109-112
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• 1994

In this Paper, we had investigated the optimal discharge condition (parameters of this experiment) in Facing Targets Sputtering System and AIN thin film. The parameters of this study are diameter of wing and electrode distance between two facing targets. If the parameters are varied, the discharge characteristics will be varied. So, we proved the optimal parameters of this experiment. Under this optimal parameter, thin film formed, and then growth rate investigated.

• International conference on construction engineering and project management
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• 2009.05a
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• pp.1307-1312
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• 2009

Design is an act based on multidisciplinary information. The involvement of various stakeholders makes it difficult to process, plan, and integrate. Iteration is frequent in most of the engineering design and development projects including construction. Design iterations cause rework, and extra efforts are required to get the optimal sequence and to manage the projects. The simple project management techniques are insufficient to fulfill the requirements of integrated design. This paper entails two things: design structure matrix and design parameters' information based model. The emphasis has been given to optimal sequence and crucial iteration using design structure matrix analysis technique. The design projects have been studied using survey data from industry. The optimal sequence and crucial iterations results have been utilized for proposed model. Model integrates two things: information about produced- required key design parameters and information of design changes during the design process. It will help to get familiar with Design management in order to fulfill contemporary needs.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.7
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• pp.3142-3150
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• 2013

Present research deals with an optimal design of the C-type frame of a desktop pressing machine to minimize its deformation which plays an important role in accuracy of the machine. Deformation pattern of the frame is analyzed by the finite element method. Design parameters are defined for the frame to derive an optimal design. Displacement and weight sensitivities of the parameters are analyzed using the method of the parametric study. On the basis of the response curves for the parameters, optimal designs of the frame are proposed. Effectiveness of the optimal design is verified by analyses in the viewpoint of the deformation and weight of the frame. Deformation of the optimized frame without increase of the weight is 87.5 % of the original frame.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.1
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• pp.58-69
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• 2014

This paper proposes a method for predicting maximum friction coefficients and optimal slip ratios as optimal control parameters for traction control or slip control of autonomous mobile robots on rough terrain. This paper focuses on strength of ground surface which indicates different characteristics depending on material types on surface. Strength of various material types can be estimated by Willoughby sinkage model and by a developed testbed which can measure forces, velocities, and displacements generated by wheel-terrain interaction. Estimated strength is collaborated on building improved Brixius model with friction-slip data from experiments with the testbed over sand and grass material. Improved Brixius model covers widespread material types in outdoor environments on predicting friction-slip characteristics depending on strength of ground surface. Thus, a prediction model for obtaining optimal control parameters is derived by partial differentiation of the improved Brixius model with respect to slip. This prediction model can be applied to autonomous mobile robots and finally gives secure maneuverability on rough terrain. Proposed method is verified by various experiments under similar conditions with the ones for real outdoor robots.