• Journal of applied mathematics & informatics
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• 제18권1_2호
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• pp.591-601
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• 2005

The results of fuzzy linear regression are very sensitive to irregular data. When this points exist in a set of data, a fuzzy linear regression model can be incorrectly interpreted. The purpose of this paper is to detect irregular data and to propose robust fuzzy linear regression based on M-estimators with triangular fuzzy regression coefficients for crisp input-output data. Numerical example shows that irregular data can be detected by using the residuals based on M-estimators, and the proposed robust fuzzy linear regression is very resistant to this points.

• Journal of the Korean Statistical Society
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• 제36권4호
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• pp.557-578
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• 2007

In Response Surface Methodology (RSM), rotatability is a natural and highly desirable property. For second order general correlated regression model, the concept of robust rotatability was introduced by Das (1997). In this paper a new measure of robust rotatability for second order response surface designs with correlated errors is developed and illustrated with an example. A comparison is made between the newly developed measure with the previously suggested measure by Das (1999).

• 한국기계가공학회지
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• 제7권3호
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• pp.3-11
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• 2008

Robust design pioneered by Dr. G. Taguchi has been applied to versatile engineering problems for improving quality. Since 1980s, the Taguchi method has been introduced to numerical optimization, complementing the deficiencies of deterministic optimization, which is often called the robust optimization. In this study, the robust optimization strategy is proposed by considering the robustness of objective and constraint functions. The statistics of responses in the functions are surrogated by kriging models. In addition, objective and/or constraint function is represented by the probability of success, thus facilitating robust optimization. The mathematical problem and the two-bar design problem are investigated to show the validity of the proposed method.

• International Journal of Automotive Technology
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• 제7권7호
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• pp.859-866
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• 2006

This study employed the perturbation method, the Edgeworth series, the reliability optimization, the reliability sensitivity technique and the robust design to present a practical and effective approach for the robust reliability design of vehicle components with arbitrary distribution parameters on the condition of known first four moments of original random variables. The theoretical formulae of the robust reliability design for vehicle components with arbitrary distribution parameters are obtained. The reliability sensitivity is added to the reliability optimization design model and the robust reliability design is described as a multi-objection optimization. On the condition of known first four moments of original random variables, the respective program can be used to obtain the robust reliability design parameters of vehicle components with arbitrary distribution parameters accurately and quickly.

• 전자공학회논문지S
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• 제34S권1호
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• pp.43-53
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• 1997

A robust stability condition for linear systems with time delay in all variables and parameter uncertainties in all system matrices is derived. Robust performance condition that accounts for robust model-matching of closed loop system and disturbance rejection is also derived. Using the robust performance condition, robust $H^{\infty}$ controller and .mu.(sgructured singular value) controller with two-degree-of-freedom(2DOF) are designed. The controller structure is considered for $H^{\infty}$ controller, while uncertainity structure is considered for .mu. controller. Using the proposed method, $H^{\infty}$ and .mu. controllers for underwater vehicle with time delay and parameter variations are designed. Simulations of a design example with hydrodynamic parameter variations and disturbance are presented to demonstrate the achievement of good robust performance.ce.

• 제어로봇시스템학회논문지
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• 제10권1호
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• pp.10-14
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• 2004

We present a predictive control algorithm combined with the robust robot control that is constructed on the Lyapunov min-max approach. Since the control design of a real manipulator system may often be made on the basis of the imperfect knowledge about the model, it is an important trend to design a robust control law that guarantees the desired properties of the manipulator under uncertain elements. In the preceding robust control work, we need to tune several control parameters in the admissible set where the desired stability can be achieved. By introducing an optimal predictive control technique in robust control we can find out much more deterministic controller for both the stability and the performance of manipulators. A new class of robust control combined with an optimal predictive control is constructed. We apply it to a simple type of 2-link robot manipulator and show that a desired performance can be achieved through the computer simulation.

• 제어로봇시스템학회논문지
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• 제7권12호
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• pp.1031-1035
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• 2001

In this paper, a robust recursive control approach for nonlinear system, which is based on Lyapunov stability, is proposed. The proposed method can apply to extended systems including cascaded systems and the stability is guaranteed in the sense of Lyapunov. The recursive design procedure so called “robust recursive control approach” is used to find a stabilizing robust controller and simultaneously estimate the uncertainty parameters. First, a nonlinear model with uncertainties whose bounds are unknown is derived. Then, unknown bounds of uncertainties are estimated. By using these estimates, the stabilizing robust controller is updated at each step. This approach is applied to the pitch autopilot design of a nonlinear missile system and simulation results indicate good performance.

• 대한전기학회논문지:전력기술부문A
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• 제48권8호
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• pp.987-995
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• 1999

A new robust controller design methodology for single-input single-output systems is proposed, where the proposed controller consists of a conventional or optimal servo controller at the outer loop as well as the robust internal-loop compensator(RIC) to eliminate the model uncertainty and external disturbance. It is shown that RIC with finite gain can make actual systems be nominal models within a prespecified error bound. And, it is also shown that RIC-based system is robustly stable regardless of input saturation. Several numerical examples are illustrated to show validities of the proposed robust controller.

• 한국지능시스템학회:학술대회논문집
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• 한국지능시스템학회 2007년도 추계학술대회 학술발표 논문집
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• pp.341-344
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• 2007

This paper proposes an alternative robust adaptive high-gain fuzzy observer design scheme and its application to synchronization of chaotic systems. The structure of the proposed observer is represented by Takagi-Sugeno fuzzy model and has the integrator of the estimation error. This improves the performance of high-gain observer and makes the proposed observer robust against noisy measurements, uncertainties and parameter perturbations as well. Using Lyapunov stability theory, an adaptive law is derived and the stability of the proposed observer is analyzed. Some simulation result is given to present the validity of theoretical derivations and the performance of the proposed observer.

• 동력기계공학회지
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• 제9권2호
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• pp.65-72
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• 2005

A new approach is presented to design a robust sampled-data controller for an experimental flexible beam carrying an unknown payload at its free end. The purpose of this paper is to move the free end of the beam to a desired position in the specified time under vibration suppression. We derive a transfer function nominal model for the beam and quantitative description of model uncertainties based on experimentally obtained frequency response data. Robust controllers are designed by applying the sampled-data $H_{\infty}$ control and ${\mu}m-theory$, in which two types of uncertainties, structured and unstructured uncertainties, are adopted for satisfactory performance in terms of hinge position regulation and vibration damping, besides obviously asymptotic stability. The effectiveness of the proposed method is confirmed through simulation and experimentation.