• Journal of the Korean Society of Manufacturing Process Engineers
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• v.11 no.2
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• pp.125-136
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• 2012

Wrinkle and fracture are two major defects frequently found in the sheet metal forming process. In this process there are more than one design attributes to optimize and several uncontrollable factors which cannot be ignored in determining the optimal values of design variables. Therefore, attempts to reduce defects through a traditional optimization technique are often led to failures. In this research, a new design method for reducing the wrinkle and fracture under uncontrollable factors is presented by using decision-making theory. To avoid the psychological difficulties in determining the scaling constants of the multi-attribute utility function by using the ordinary lottery questions, a pair-wise comparison procedure is adapted to avoid this problem. The effectiveness of the proposed method is illustrated through a robust design of sheet metal forming process of a side member of an automotive body.

• 한국신재생에너지학회:학술대회논문집
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• 2009.11a
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• pp.427-430
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• 2009

풍력 터빈 블레이드용 익형의 경우 운용 조건에서 높은 양항비를 가지도록 설계되나 풍속, 풍향의 변동에 의해 운용조건에 변화가 발생할 경우 성능의 저하가 발생할 수 있다. 따라서 운용조건의 변동이 발생하더라도 공력 성능이 크게 변하지 않는 익형이 요구된다. 본 연구에서는 이러한 운용조건의 불확실성을 고려하여 풍력 터빈 블레이드용 익형의 신뢰성 기반 강건 최적 설계를 수행하였다. 익형 설계를 위해서 여러 익형 형상 변수들을 고려할 수 있는 익형 모델링 함수를 정의하였고 기저형상으로는 NREL에서 개발한 S809 익형을 사용하였다.

• Journal of the Korean Society of Industry Convergence
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• v.12 no.1
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• pp.35-42
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• 2009

In Taguchi's quadratic expected loss function used as robustness metric of performance characteristics, the mean and variance contributions are confounded. The consolidation of the mean and variance in the expected loss function may not always be the ideal approach. This paper presents a procedure for multi-attributes design optimization, where the mean and variance of performance characteristics are considered as separate attributes having designer's relative preferences for them and Technique for Order Preference by Similarity to Ideal Solution(TOPSIS) is introduced to attain robust optimal design. The effectiveness of proposed approach is shown with an example of a weld line minimization problem in the injection molding process.

• Earthquakes and Structures
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• v.1 no.3
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• pp.289-306
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• 2010

A gradient-based evolutionary optimization methodology is presented for finding the optimal design of viscous dampers to minimize an objective function defined for a linear multi-storey structure. The maximum value along height of the transfer function amplitudes for the interstorey drifts is taken as the objective function. Since the ground motion includes various uncertainties, the optimal damper placement may be different depending on the ground motion used for design. Furthermore, the transfer function treated as the objective function depends on the properties of structural parameters and added dampers. This implies that a more robust damper design is desired. A reliable and robust damping design system against any unpredictable ground motions can be provided by minimizing the maximum transfer function. Such design system is proposed in this paper.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2389-2391
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• 2000

To design high quality products at low cost is one of very important tasks for engineers. Design optimization for performances can be one solution in this task. There is the robust design which has been proved effectively in many fields of engineering design. In this paper, the concept of robust design is introduced and combined to the fuzzy optimization method and the fuzzy logic system method with non-singleton. These methods are applied for data analysis to get optimum parameters and to reduce experiments. The optimum parameter set points are obtained by the proposed methods. These methods are applied to a filter circuit, a part of the audio circuit of mobile radio transceiver. The simulation results are compared each other. The new methods reduce and predict the effect of parameter variation sources

• Journal of the military operations research society of Korea
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• v.28 no.1
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• pp.47-66
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• 2002

Instead of using signal-to-noise ratio, we attempt to optimize both the mean and variance responses using dual response optimization technique. The alternative experimental strategy analyzes a robust parameter design problem to obtain the best settings that give a target condition on the mean while minimizing its variance. The mean and variance are treated as the two responses of interest to be optimized. Unlike to the crossed array and combined array approaches, our experimental setup requires replicated runs for each control factor's treatment under noise sampling. When the postulated response models are true, they enable the coefficients to be estimated and the desired performance measure to be analyzed more efficiently. The procedure and illustrative example are given for the dual response optimization techniques of nonlinear goal programming.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.29 no.1 s.232
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• pp.59-66
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• 2005

In this paper, a robust stationary Kalman filter is designed by minimizing selected performance indices so that it is less sensitive to uncertainties. The uncertainties include not only stochastic factors such as process noise and measurement noise, but also deterministic factors such as unknown initial estimation error, modeling error and sensing bias. To reduce the effect on the uncertainties, three performance indices that should be minimized are selected based on the quantitative error analysis to both the deterministic and the stochastic uncertainties. The selected indices are the size of the observer gain, the condition number of the observer matrix, and the estimation error variance. The observer gain is obtained by optimally solving the multi-objectives optimization problem that minimizes the indices. The robustness of the proposed filter is demonstrated through the comparison with the standard Kalman filter.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.48.3-48
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• 2001

A gain-scheduled autopilot design for a bank-to-turn (BTT) missile is developed by using the Linear Matrix Inequality (LMI) optimization technique and a state-space lineal interpolation method. The missile dynamics are brought to a quasilinear parameter varying (quasi-LPV) form. Robust linear control design method is used to obtain state feedback controllers for the LPV systems with exogenous disturbances at the frozen values of the scheduling parameters. Two gam-scheduled controllers for the pitch axis and the yaw/roll axis are constructed by linearly interpolating the robust state-feedback gains. The designed controller is applied to a nonlinear six-degree-of-freedom (6-DOF) simulations.

• Journal of the Korean Mathematical Society
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• v.59 no.6
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• pp.1153-1170
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• 2022

In this paper, we investigate the portfolio optimization problem under the SVCEV model, which is a hybrid model of constant elasticity of variance (CEV) and stochastic volatility, by taking into account of minimum-entropy robustness. The Hamilton-Jacobi-Bellman (HJB) equation is derived and the first two orders of optimal strategies are obtained by utilizing an asymptotic approximation approach. We also derive the first two orders of practical optimal strategies by knowing that the underlying Ornstein-Uhlenbeck process is not observable. Finally, we conduct numerical experiments and sensitivity analysis on the leading optimal strategy and the first correction term with respect to various values of the model parameters.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2023.05a
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• pp.254-255
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• 2023

This paper discovers a robust managerial strategy for a stochastic inventory of perishable products, where the model experiences changing factors including inner parameters and an external disturbance with unknown form. An analytical solution for the optimization problem can be obtained by applying the Hamilton-Bellman-Jacobi equation, however the policy result cannot completely suppress the oscillation from the external disturbance. Therefore, an intelligent approach named Radial Basis Function Neural Networks is applied to estimate the unknown disturbance and provide a robust controller to manipulate the inventory level more effective. The final results show the outstanding performance of RBFNN controller, where both the estimation error and control error are guaranteed in the predefined limit.