• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.498-498
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• 2000

A study on the robust control of a composite beam with a distributed PVDF sensor and piezo-ceramic actuator is presented in this paper. 1st and 2nd natural frequencies are considered in the modeling, because robust control theory which has robustness to structured uncertainty is adopted to suppress the vibration. If the controllers designed by H$_{\infty}$ theory do not satisfy control performance, it is improved by $\mu$-synthesis method with D-K iteration so that the $\mu$-controller based on the structured singular value satisfies the nominal performance and robust performance. Simulation and experiment were carried out with the designed controller and the verification of the robust control properties was presented by results.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.326-326
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• 2000

Continuous time system deadbeat controller(CdbC) has been studied mainly since 1992 especially by Japan researchers. They suggested delay elements. These elements stem from the finite Laplace Transform which is the starting point in deadbeat control system design in continuous time system. Every transfer function is established by these elements. From some conditions such as internal model stability and peasibility of a CdbC controller. unknown polynomials or coefficients can be calculated. In this paper, optimal pole placement of the closed loop system is suggested. From this. a CdbC controller with lower order can be obtained which attains the same level of weighted sensitivity function's H$_{\infty}$ norm used as a measure of the robustness property as existing CdbCs.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.11a
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• pp.301-305
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• 1996

$\mu$ theory can handle the parametric uncertainty and produces more non-conservative controller than H$_{\infty}$ control theory. However an existing solution of the theory, D-K iteration, creates a controller of huge order and cannot handle the real or mixed real-complex perturbation sets. In this paper, we use genetic algorithms to solve these problems of the D-K iteration method. The Youla parameterization is used to obtain all stabilizing controllers and the genetic algorithms determines the values of the state feedback gain, the observer gain, and Q parameter to minimize $\mu$, the structured singular value, of given system. From an example, we show that this method produces lower order controller which controls a real parameter-perturbed plant than D-K iteration method.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2002.05a
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• pp.740-745
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• 2002

To control vibration of real-size steel structure, a hybrid-type linear motor damper was designed and applied to 30m steel structure at UNISON. The LMD was tuned to the first mode natural frequency of the building. In order to use for simulation data and control parameters, dynamic response characteristics of building and damper were tested. The response of building was reduced by 10 dB with LMD and H$\infty$ algorithm. This value was similar to the result of simulation.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.25 no.2
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• pp.242-249
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• 2001

In this study, a methodology of synchronous control has been developed that can is applied to position synchronization of a two-axes driving system such as overhead crane. The synchronous error is caused by model uncertainties and torque load at each axis. To overcome these problems, the synchronous control system has been composed of two disturbance observers to calculate the torque disturbance and one synchronous controller to eliminate synchronous error. By considering model uncertainties of each axis, the synchronous controller has been designed using H(sub)$\infty$ control theory. The effectiveness of the proposed method has been verified through simulation.

• International Journal of Aeronautical and Space Sciences
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• v.2 no.2
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• pp.73-81
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• 2001

This paper describes the procedure to develop a robust estimator design method for a target tracker that accounts for both structured real parameter uncertainties and unknown inputs. Two robust design approaches are combined: the Mini-p-Norm. design method to consider real parameter uncertainties and the $H_{\infty}$ design technique for unknown disturbances and unknown inputs. Constant estimator gains are computed that guarantee the robust performance of the estimator in the presence of parameter variations in the target model and unknown inputs to the target. The new estimator has two design parameters. One design parameter allows the trade off between small estimator error variance and low sensitivity to unknown parameter variations. Another design parameter allows the trade off between the robustness to real parameter variations and the robustness to unknown inputs. This robust estimator design method was applied to the longitudinal motion tracking problem of a T-38 aircraft.

• Proceedings of the KIEE Conference
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• 1998.07b
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• pp.449-451
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• 1998

In this paper, we consider the problem of the robust stability of uncertain linear systems with multiple time-varying delays. The considered uncertainties are both the unstructured uncertainty which is only known its norm bound and the structured uncertainty satisfying the matching conditions, respectively. We present conditions that guarantee the robust stability of systems based on Lyapunov stability theorem and $H_{\infty}$ theory in the time domain. Finally, we show the usefulness of our results by numerical examples.

• The Korean Journal of Malacology
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• v.29 no.1
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• pp.43-50
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• 2013

We investigated the growth performance of oysters (initial shell height $57.5{\pm}8.5$ mm) under differing conditions of tidal exposure time and culture rack height in an experiment that commenced in April, 2011. Significant differences were observed in shell height from June 2011, in total weight from August, and in meat weight from September. Fatness tended to decrease during the experimental period, but was not significantly different at the end of the experiment. Significant differences in survival rates were mainly observed from June to August. After September, further changes were not observed in any experimental treatment group. The greatest growth potential ($L_{\infty}$) and survival rate were observed at a sea level of approximately 116 cm. The results indicate that in the study area the use of oyster culture conditions involving 1 or 2 h of tidal exposure and 60 - 70 cm rack height could result in oysters reaching the favored commercial half shell size within 14 months, with > 80% survival.

• Proceedings of the Korean Nuclear Society Conference
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• 1997.10a
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• pp.293-298
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• 1997

The H$_{\infty}$robust controller fur the reactor power control system is designed by use of the mixed weight sensitivity. The system is configured into the typical two-port model with which the weight functions are augmented. Since the solution depends on the weighting functions and the problem is of non-convex, the genetic algorithm is used to determine the weighting functions. The cost function applied in the genetic algorithm permits the direct control of the power tracking performances. In addition, the actual operating constraints such as rod velocity and acceleration can be treated as design parameters. Compared with the conventional approach, the controller designed by the genetic algorithm results in the better performances with the realistic constraints. Also, it is found that the genetic algorithm could be used as an effective tool in the robust design. robust design.

• Proceedings of the IEEK Conference
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• 2000.07a
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• pp.395-398
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• 2000

The method of Variable Structure Control (VSC) design of windmill power systems is proposed. In the design of sliding mode control, we use Riccati equations arising in linear H$\^$$\infty$/ control to decide a stable sliding surface. Then the reachability to the sliding surface is realized by designing a nonlinear controller for the windmill power system. The capability of the proposed controller to damp out the oscillations of power and the robustness with respect to the system parameter variations and model errors are evaluated in the simulation study.