• The Transactions of the Korean Institute of Electrical Engineers
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• v.37 no.3
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• pp.180-185
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• 1988

This paper considers the problem of the optimal input design for parameter estimtion in the ARMAX model in which the system and noise transfer function have the common denominator polynomial. Deriving the information matrix, in detail, for the assumed model structure and using the autocorrelation functin of the filtered input as design variables, it is shown that D-optimal input signal can be realized as an autoregressive moving average process. Computer simulations are carried out to show the standard-deviation reduction in the parameter estimtes using the optimal input signal.

• Journal of Welding and Joining
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• v.11 no.3
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• pp.34-47
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• 1993

Finite element models were developed for thermal and residual stress analysis for the specific welding problems. They were used to evaluate the effectiveness of the various welding heat input models, such as ramp heat input function and lumped pass models. Through the parametric studies, thermal-mechanical modeling sensitivity to the ramp function and lumping techniques was determined by comparing the predicted results with experimental data. The kinetics for residual stress formation during welding can be developed by iteration of various proposed mechanisms in the parametric study. A ramp heat input function was developed to gradually apply the heat flux with variable amplitude to the model. This model was used to avoid numerical convergence problems due to an instantaneous increase in temperature near the fusion zone. Additionally, it enables the model to include the effect of a moving arc in a two-dimensional plane. The ramp function takes into account the variation in the out of plane energy flow in a 2-D model as the arc approaches, travels across, and departs from each plane under investigation. A lumped pass model was developed to reduce the computation cost in the analysis of multipass welds. Several weld passes were assumed as one lumped pass in this model. Recommendations were provided about ramp lumping techniques and the optimum number of weld passes that can be combined into a single thermal input.

• Geomechanics and Engineering
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• v.12 no.2
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• pp.239-255
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• 2017

Various centrifuge model tests on the pile foundations were performed to investigate fundamental characteristics of a pile-soil-foundation system recently, but it is hard to find numerical analysis results of a pile foundation system considering the nonlinear behavior of soil layers due to the dynamic excitations. Numerical analyses for a pile-soil system were carried out to verify the experimental results of centrifuge model tests. Centrifuge model tests were performed at the laboratory applying 1.5 Hz sinusoidal base input motions, and nonlinear numerical analyses were performed utilizing a finite element program of P3DASS in the frequency domain and applying the same input motions with the intensities of 0.05 g~0.38 g. Nonlinear soil properties of soil elements were defined by Ramberg-Osgood soil model for the nonlinear dynamic analyses. Nonlinear numerical analyses with the P3DASS program were helpful to predict the trend of experimental responses of a centrifuge model efficiently, even though there were some difficulties in processing analytical results and to find out unintended deficits in measured experimental data. Also nonlinear soil properties of elements in the system can be estimated adequately using an analytical program to compare them with experimental results.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2006.05a
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• pp.1707-1714
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• 2006

In order to enhance sustainable war fighting capabilities, it is important to maintain a good ammunition support system. In this paper, we evaluate the performance of Ammunition companies using Imprecise Data Envelopment Analysis (IDEA)-BCC and IDEA-Additive model, which can deal with imprecise data in DEA. In order to select a list of input and output variables, we used a multiple regression analysis. We could choose input variables that have significant effects on the output performance with stepwise regression model. From the regression analysis, the number of soldiers, officers, and ammunition warehouses were selected as the input variables. Seven out of sixteen Ammunition companies were found to be inefficient by the IDEA-BCC model. And using IDEA-Additive model, we could identify the input excess and the output shortfall in reaching at a point on the efficiency frontier.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.5
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• pp.607-614
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• 1999

This paper deals with the design problem of the state estimator for servo system. The servo system has input time delay which depends on the computational time of control algorithm. The delayed input is a factor that brings out the state estimation error. So in order to reduce the state estimation error of the system, we propose a state estimator in which the delayed input of the system is considered. For this purpose, discrete time state space model is established accounting for the delayed input and a state estimator is designed based on this model. Kalman filter algorithm is employed in the design of the state estimator. The proposed estimator is used in the speed control of servo system with delayed input. Performance of the proposed state estimator is exemplified via simulations and experiments for servo system. Also, robustness of the proposed estimator to modeling error by variation of the system parameters is also shown in simulations.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.10a
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• pp.123-128
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• 1998

This paper proposes design of LFT-based fuzzy controllers for model-following, which are better than the previous input-output linearization controllers, which are not able to follow the model system states and which do not guarantee the stability of all states. The method proposed in this paper provides a LFT-based Takagi-Sugeno(T-S) fuzzy controller with guaranteed stability and model-following via the following steps: First, using LFT(Linear Fractional Transformation) and T-S fuzzy model, controllers, are obtained. Next, error dynamics are obtained for model-following, and errors go to 0(zero). Finally, a T-s fuzzy controller that can stabilizxe the system with the requirement on the control input satisfied is obtained by solving the LMIs with the MATLAB LMI Control Toolbox and a model-following controller is obtained. Simulations are performed for the LFT-based T-S fuzzy controller designed by the proposed method, which show better performance than the results of input-out ut linearization controller.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2000.05a
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• pp.47-50
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• 2000

In this paper, an optimal identification method using Multi-FNN(Fuzzy-Neural Network) is proposed for model ins of nonlinear complex system. In order to control of nonlinear process with complexity and uncertainty of data, proposed model use a HCM clustering algorithm which carry out the input-output data preprocessing function and Genetic Algorithm which carry out optimization of model. The proposed Multi-FNN is based on Yamakawa's FNN and it uses simplified inference as fuzzy inference method and Error Back Propagation Algorithm as learning rules. HCM clustering method which carry out the data preprocessing function for system modeling, is utilized to determine the structure of Multi-FNN by means of the divisions of input-output space. Also, the parameters of Multi-FNN model such as apexes of membership function, learning rates and momentum coefficients are adjusted using genetic algorithms. Also, a performance index with a weighting factor is presented 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 and the numerical data of nonlinear function.

• IE interfaces
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• v.19 no.4
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• pp.291-299
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• 2006

In order to enhance sustainable war fighting capabilities, it is important to maintain a good ammunition support system. In this paper, we evaluate the performance of ammunition companies using Imprecise Data Envelopment Analysis (IDEA)-BCC and IDEA-Additive model, which can deal with imprecise data in DEA. The input variables of IDEA models were selected by stepwise multiple regression analysis. With the regression model, we could choose the number of soldiers, officers, and ammunition warehouses as input variables that have significant effects on the output performance. Then, we applied the IDEA-BCC model with the concept of potential efficiency. The results of the model indicate that 8 out of 16 ammunition companies are efficient, 7 are inefficient, and 1 is potentially efficient. We could also identify the possible input excesses and output shortfalls to reach the efficient frontier using the IDEA-Additive model.

• Journal of the Society of Naval Architects of Korea
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• v.43 no.1 s.145
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• pp.50-58
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• 2006

Free running model tests gives us only maneuvering indices not hydrodynamic derivatives. For this reason, system identification method has been applied to the measured data to identify mathematical model describing hydrodynamic force. However It is difficult to obtain complete set of maneuvering derivatives because of strong correlation of sway velocity and yaw rate. Therefore, in this paper, we assumed that sway velocity related coefficients would be obtained by oblique towing test. and then proposed new procedure to estimate yaw related coefficients. To do this, correlation and regression analyses were carried out to establish modified model and estimate maneuvering derivatives. Also D-optimal rudder input scenario was found based on the modified model and confirmed the validity of its sufficient richness as a input scenario.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.2
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• pp.1-9
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• 1998

ATM was adopted as the switching and multiplexing technique for BISDN which aims at transmitting traffics with various characteristics in a unified network. To construct these ATM networks, the most important aspect is the design of the switching system with high performance and different service capabilities. In this paepr, we analyze the performance of an input and output queueing switch with preemptive priority which is considered to be most suitable for ATM networks. For the analysis of an input queue, we model each input queue as two separate virtual input queues for each priority class and we approximage them asindependent Geom/Geom/1 queues. And we model a virtual HOL queue which consists of HOL cells of all virtual input queues which have the same output address to obtain the mean service time at each virtual input queue. For the analysis of an output quque, we obtain approximately the arrival process into the output queue from the state of the virtual HOL queue. We use a Markov chain method to analyze these two models and obtain the maximum throughput of the switch and the mean queueing delay of cells. and analysis results are compared with simulation to verify that out model yields accurate results.