• The Korean Journal of Applied Statistics
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• v.25 no.3
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• pp.485-501
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• 2012

This research is to find a design D that minimizes forecast variance in d dimensions over the candidate space ${\chi}$. We want a robust design since we may not know the specific covariance structure. We seek a design that minimizes a coverage criterion and hope that this design will provide a small forecast variance even if the covariance structure is unobservable. The details of an exchange or swapping algorithm and several properties of the parameters of coverage criterion with the unknown correlation structures are discussed.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.642-647
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• 1993

In general, systems contain uncertain elements in the real world; these may be parameters, constant or varying, that are unknown or imperfectly known. When the uncertainty is assumed to satisfy the matching condition and to be cone-bounded, Y.H. Chen[81 proposed an adaptive robust control algorithm which introduced adaptive scheme for a design parameter into robust deterministic controls. In this paper, the above control algorithm is applied to the position tracking control of 2 DOF direct drive SCARA robots, and simulation and experimental studies are conducted to verify the control algorithm and to evaluate control performance.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.1492-1495
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• 1996

In this paper, an approach to autopilot design based on the robust nonlinear dynamic inversion method is proposed. Both unknown parameters and uncertainty bounds are estimated and parameter estimates are used in the fast inversion. Furthermore, to get more robustness slow inversion is incorporated with MRAC(Model Reference Adaptive Control) and sliding mode control where the estimates of uncertainty bounds are used. The proposed method is applied to the pitch autopilot design of a missile system and excellent performance is shown via computer simulation.

• Journal of the Korean Data and Information Science Society
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• v.18 no.2
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• pp.471-479
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• 2007

This paper discusses about how to build up mixed-effects model for analysing ordinal response data by using cumulative logits. Random factors are assumed to be coming from the designed sampling scheme for choosing observational units. Since the observed responses of individuals are ordinal, a proportional odds model with two random effects is suggested. Estimation procedure for the unknown parameters in a suggested model is also discussed by an illustrated example.

• Journal of the Korean Data and Information Science Society
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• v.25 no.4
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• pp.921-929
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• 2014

A bivariate exponential distribution with a location parameter is proposed as a model for a two-component shared load system with a guarantee time. Some statistical properties of the proposed model are investigated. The maximum likelihood estimators and uniformly minimum variance unbiased estimators of the parameters, mean time to failure, and the reliability function of system are obtained with unknown guarantee time. Simulation studies are given to illustrate the results.

• Journal of information and communication convergence engineering
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• v.6 no.1
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• pp.86-90
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• 2008

In this paper, I have presented a new approach which can track moving objects in unknown environments. This scheme is important in providing a computationally feasible alternative to complete enumeration of JPDA which is intractable. I have proved that given an artificial measurement and track's configuration, proposed scheme converges to a proper plot in a finite number of iterations. In this light, even if the performance is enhanced by using the relaxation, we also note that the difficulty in tuning the parameters of the relaxation scheme is critical aspect of this suggestion.

• Proceedings of the KIEE Conference
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• 1989.07a
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• pp.57-61
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• 1989

An adaptive control scheme is presented for uncertain systems whose uncertaintiy bounds are expressed as a linear combination of unknown functions of special form. Both the states and the parameter estimate errors of the closed-loop system are proven to be bounded. The regulation errors can be made sufficiently small by adjusting the design parameters. An application of the proposed method to the position control of a simple pendulum is given.

• Journal of Electrical Engineering and information Science
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• v.3 no.1
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• pp.36-44
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• 1998

In this paper, a robust adaptive sliding mode control algorithm for accurate trajectory tracking of robot manipulators is proposed, with unknown parameters being estimated on-line. The controller is designed based on a Lyapunov method, which consists of adaptive feed-forward compensation part and a discontinuous control part. It is shown that, in the presence of the uncertainty and the disturbances arising from the actuator or some other causes, the tracking errors is bound to converge to zero asymptotically. An illustrative example is given to demonstrate the results of the propose method.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.83.5-83
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• 2002

Perspective dynamical systems arise in machine vision, in which only perspective observation is available, and the essential problem is to estimate the state and /or unknown parameters for a moving rigid body based on the observed information. This paper proposes and studies a Luenberger-type observer for perspective tim e-varying linear systems. In particular, assuming a given perspective time-varying linear system to be Lyapunov stable and to satisfy some sort of observability condition, it is shown that the estimation error converges exponentially to zero. Finally, a simple numerical exam pie is presented to illustrate the result obtained.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.990-995
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• 1991

The integration of intelligent robots into manufacturing systems should positively impact the product quality and productivity. A new theory of object location and recognition using the supporting plane is presented. The unknown supporting points are determined by image coordinates, known camera parameters, and joint coordinates of the robot manipulators. This is developed by using the geometrical interpretation of perspective projection and the geometrical constraints of industrial environments. This can be applied to solve typical robot vision problems such as determination of position, orientation, and recognition of objects.