• Korean Journal of Mathematics
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• v.26 no.2
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• pp.155-166
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• 2018

Consider FARIMA time series with innovations that have infinite variances. We are interested in the estimation of self-similarities $H_n$ of FARIMA(0, d, 0) by using modified R/S statistic. We can confirm that the $H_n$ converges to Hurst parameter $H=d+\frac{1}{2}$. Finally, we figure out ARMA and minimum variance power spectrum density of FARIMA processes.

• Proceedings of the KIEE Conference
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• 1993.07a
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• pp.355-358
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• 1993

This paper introduces what calibration is and how it is operated. The steps of calibration methods are discussed, which are modeling, measurement, parameter identification and compensation. Using modified D-H model, a new algorithm for parameter identification is developed. This algorithm is very simple and applicable to off-line robot simulator.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.542-547
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• 2003

A new approach to design of a discrete-time robust $H_{\infty}$ filter in finite horizon case is proposed. It is shown that robust $H_{\infty}$ filtering problem can be cast into the minimization problem of an indefinite quadratic form, which can be solved by implementing the Kalman filter defined in Krein space. The proposed filter is readily derived by simply augmenting the state space model and has the robustness property against the parameter uncertainties of a given system.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.54 no.1
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• pp.11-16
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• 2005

This paper considers a robust observer-based H/sub ∞/ controller design method for singular systems with parameter uncertainties using an LMI condition. The sufficient condition for the existence of controller and the controller design method are presented by a perfect LMI condition in terms of all variables using singular value decomposition, Schur complement, and change of variables. Therefore, one of the main advantages is that a robust observer-based H/sub ∞/ controller can be established by solving one LMI condition compared with existing results. Numerical example is given to illustrate the effectiveness of the proposed controller design method.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2005.10a
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• pp.87-90
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• 2005

The drawbead is used to control the material flow into the die and increase the forming quality during the binder wrap process and the stamping process in the sheet metal forming. Drawbead restraining force (DBRF) is controlled by geometrical parameters and influenced by process parameters such as friction coefficient and blank thickness. In order to inspect the effect of process parameters, parameter studies are performed with the variation of parameters using finite element model of drawbead which is utilized reliably for the calculation of the drawbead restraining force. Drawbead analysis is carried out with 2-D plane-strain element and 3-D shell element. After the verification of the accuracy of the drawbead model with 3-D shell element, it is utilized to the prediction and the investigation of the effect of process parameters. The result of parameter studies can be utilized to the die design in the tryout stage.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2010.05a
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• pp.349-350
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• 2010

• Proceedings of the KIEE Conference
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• 1989.07a
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• pp.12-15
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• 1989

This paper describes the efforts to develop an PC based parameter identification system for the D.C. servomotor. The whole identification process of signal generation, measuring, parameter determination is fully automated. To minimize errors due to the ripple component in the measured armature current, digital averaging filter is employed. The proposed parameter correction method using the deadzone current and the time to reach the peak current resulted in excellent agreement between the measured current and estimated current using the model.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2012.05a
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• pp.19-20
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• 2012

• Smart Structures and Systems
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• v.9 no.4
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• pp.373-392
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• 2012

Tracking control of systems with variable stiffness hysteresis using a gain-scheduled (GS) controller is developed in this paper. Variable stiffness hysteretic system is represented as quasi linear parameter dependent system with known bounds on parameters. Assuming that the parameters can be measured or estimated in real-time, a GS controller that ensures the performance and the stability of the closed-loop system over the entire range of parameter variation is designed. The proposed method is implemented on a spring-mass system which consists of a semi-active independently variable stiffness (SAIVS) device that exhibits hysteresis and precisely controllable stiffness change in real-time. The SAIVS system with variable stiffness hysteresis is represented as quasi linear parameter varying (LPV) system with two parameters: linear time-varying stiffness (parameter with slow variation rate) and stiffness of the friction-hysteresis (parameter with high variation rate). The proposed LPV-GS controller can accommodate both slow and fast varying parameter, which was not possible with the controllers proposed in the prior studies. Effectiveness of the proposed controller is demonstrated by comparing the results with a fixed robust $\mathcal{H}_{\infty}$ controller that assumes the parameter variation as an uncertainty. Superior performance of the LPV-GS over the robust $\mathcal{H}_{\infty}$ controller is demonstrated for varying stiffness hysteresis of SAIVS device and for different ranges of tracking displacements. The LPV-GS controller is capable of adapting to any parameter changes whereas the $\mathcal{H}_{\infty}$ controller is effective only when the system parameters are in the vicinity of the nominal plant parameters for which the controller is designed. The robust $\mathcal{H}_{\infty}$ controller becomes unstable under large parameter variations but the LPV-GS will ensure stability and guarantee the desired closed-loop performance.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.51 no.4
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• pp.129-136
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• 2002

This paper presents a $H_{\infty}$ robust controller with parameter estimation in polynomial approach. For good performance of a uncertain system, the parameters are estimated by RLS algorithm. The controller minimizes the sum of $H_{\infty}$ norm between sensitivity function and complementary sensitivity function by employing the Youla parameterization and polynomial approach at the same time. A numerical example and its simulation results are given to show the validity of the proposed controller.